Publications

Last updated by: June 12, 2020

2020

  • Teng Ye, Wei Ai, Lingyu Zhang, Ning Luo, Lulu Zhang, Jieping Ye, and Qiaozhu Mei. Predicting individual treatment effects of large-scale team competitions in a ride-sharing economy. In Proceedings of the 26th ACM SIGKDD international conference on knowledge discovery and data mining, 2020.
    [BibTeX] [Download PDF]
    @inproceedings{KDD2020TeamComp,
    author = { Ye, Teng and Ai, Wei and Zhang, Lingyu and Luo, Ning and Zhang, Lulu and Ye, Jieping and Mei, Qiaozhu},
    title = {Predicting Individual Treatment Effects of Large-scale Team Competitions in a Ride-sharing Economy},
    booktitle = {Proceedings of the 26th {ACM} {SIGKDD} International Conference on Knowledge Discovery and Data Mining},
    pages = {},
    year = {2020},
    url = {http://www.yelabs.net/publications/2020_kdd_TeamComp.pdf}
    }

  • Huiting Hong, Yucheng Lin, Xiaoqing Yang, Zang Li, Kun Fu, Zheng Wang, Xiaohu Qie, and Jieping Ye. HetETA: heterogeneous information network embedding for estimating time of arrival. In Proceedings of the 26th ACM SIGKDD international conference on knowledge discovery and data mining, 2020.
    [BibTeX] [Download PDF]
    @inproceedings{KDD2020HetETA,
    author = {Hong, Huiting and Lin, Yucheng and Yang, Xiaoqing and Li, Zang and
    Fu, Kun and Wang, Zheng and Qie, Xiaohu and Ye, Jieping},
    title = {{HetETA}: Heterogeneous Information Network Embedding for
    Estimating Time of Arrival},
    booktitle = {Proceedings of the 26th {ACM} {SIGKDD} International Conference on Knowledge Discovery and Data Mining},
    pages = {},
    year = {2020},
    url = {http://www.yelabs.net/publications/2020_kdd_HetETA.pdf}
    }

  • Wenjuan Luo, Han Zhang, Xiaodi Yang, Lin Bo, Xiaoqing Yang, Zang Li, Xiaohu Qie, and Jieping Ye. Dynamic heterogeneous graph neural network for real-time event prediction. In Proceedings of the 26th ACM SIGKDD international conference on knowledge discovery and data mining, 2020.
    [BibTeX] [Download PDF]
    @inproceedings{KDD2020HGNN,
    author = { Luo, Wenjuan and
    Zhang, Han and
    Yang, Xiaodi and
    Bo, Lin and
    Yang, Xiaoqing and
    Li, Zang and
    Qie, Xiaohu and
    Ye, Jieping},
    title = {Dynamic Heterogeneous Graph Neural Network for Real-time Event Prediction},
    booktitle = {Proceedings of the 26th {ACM} {SIGKDD} International Conference on Knowledge Discovery and Data Mining},
    pages = {},
    year = {2020},
    url = {http://www.yelabs.net/publications/2020_kdd_HGNN.pdf}
    }

  • Che Liu, Junfeng Jiang, Chao Xiong, Yi Yang, and Jieping Ye. Towards building an intelligent chatbot for customer service: learning to respond at the appropriate time. In Proceedings of the 26th ACM SIGKDD international conference on knowledge discovery and data mining, 2020.
    [BibTeX] [Download PDF]
    @inproceedings{KDD2020CS,
    author = { Liu, Che and
    Jiang, Junfeng and
    Xiong, Chao and
    Yang, Yi and
    Ye, Jieping},
    title = {Towards Building an Intelligent Chatbot for Customer Service:
    Learning to Respond at the Appropriate Time},
    booktitle = {Proceedings of the 26th {ACM} {SIGKDD} International Conference on Knowledge Discovery and Data Mining},
    pages = {},
    year = {2020},
    url = {http://www.yelabs.net/publications/2020_kdd_CS.pdf}
    }

  • Kun Fu, Fanlin Meng, Jieping Ye, and Zheng Wang. CompactETA: a fast inference system for travel time prediction. In Proceedings of the 26th ACM SIGKDD international conference on knowledge discovery and data mining, 2020.
    [BibTeX] [Download PDF]
    @inproceedings{KDD2020CompactETA,
    author = { Fu, Kun and Meng, Fanlin and Ye, Jieping and Wang, Zheng},
    title = {{CompactETA}: A Fast Inference System for Travel Time Prediction},
    booktitle = {Proceedings of the 26th {ACM} {SIGKDD} International Conference on Knowledge Discovery and Data Mining},
    pages = {},
    year = {2020},
    url = {http://www.yelabs.net/publications/2020_kdd_CompactETA.pdf}
    }

  • Hai Yang, Chaoyi Shao, Hai Wang, and Jieping Ye. Integrated reward scheme and surge pricing in a ridesourcing market. Transportation Research Part B: Methodological, 134:126-142, 2020.
    [BibTeX] [Download PDF]
    @article{TRBIntegreatedReward2020,
    author = {Yang, Hai and Shao, Chaoyi and Wang, Hai and Ye, Jieping},
    title = {Integrated reward scheme and surge pricing in a ridesourcing market},
    journal = {{Transportation Research Part B: Methodological}},
    volume = {134},
    pages = {126-142},
    year = {2020},
    url = {https://www.sciencedirect.com/science/article/pii/S0191261519302395}
    }

  • Zhengtian Xu, Yafeng Yin, and Jieping Ye. On the supply curve of ride-hailing systems. Transportation Research Part B: Methodological, 132:29-43, 2020.
    [BibTeX] [Download PDF]
    @article{TRBSupplyCurve2020,
    author = {Xu, Zhengtian and Yin, Yafeng and Ye, Jieping},
    title = {On the supply curve of ride-hailing systems},
    journal = {{Transportation Research Part B: Methodological}},
    volume = {132},
    pages = {29-43},
    year = {2020},
    url = {https://www.sciencedirect.com/science/article/pii/S0191261518311494}
    }

  • Hai Yang, Xiaoran Qin, Jintao Ke, and Jieping Ye. Optimizing matching time interval and matching radius in on-demand ride-sourcing markets. Transportation Research Part B: Methodological, 131:84-105, 2020.
    [BibTeX] [Download PDF]
    @article{TRBOPtimizingMatching2020,
    author = {Yang, Hai and Qin, Xiaoran and Ke, Jintao and Ye, Jieping},
    title = {Optimizing matching time interval and matching radius in on-demand ride-sourcing markets},
    journal = {{Transportation Research Part B: Methodological}},
    volume = {131},
    pages = {84-105},
    year = {2020},
    url = {https://www.sciencedirect.com/science/article/pii/S0191261518311731}
    }

  • Jie Gui, Zhenan Sun, Yonggang Wen, Dacheng Tao, and Jieping Ye. A review on generative adversarial networks: algorithms, theory, and applications. CoRR, abs/2001.06937, 2020.
    [BibTeX] [Download PDF]
    @article{GANSurvey2020,
    author = {Gui,  Jie and Sun, Zhenan and Wen, Yonggang and Tao, Dacheng and
    Ye, Jieping },
    title = {A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications},
    journal = {{CoRR}},
    volume = {abs/2001.06937},
    year = {2020},
    url = {https://arxiv.org/abs/2001.06937}
    }

2019

  • Fan Zhou, Tengfei Li, Haibo Zhou, Hongtu Zhu, and Jieping Ye. Graph-based semi-supervised learning with non-ignorable non-response. In Advances in neural information processing systems, pages 7013-7023, 2019.
    [BibTeX] [Download PDF]
    @inproceedings{NeuRIPS2019SSL,
    author = {Zhou, Fan and
    Li, Tengfei and
    Zhou, Haibo and
    Zhu, Hongtu and
    Ye, Jieping },
    title = {Graph-Based Semi-Supervised Learning with Non-ignorable Non-response},
    booktitle = {Advances in Neural Information Processing Systems},
    pages = {7013--7023},
    year = {2019},
    url = {http://papers.nips.cc/paper/8924-graph-based-semi-supervised-learning-with-non-ignorable-non-response}
    }

  • Haipeng Chen Chen, Yan Jiao, Zhiwei Qin, Xiaocheng Tang, Hao Li, Bo An, Hongtu Zhu, and Jieping Ye. InBEDE: integrating contextual bandit with TD learning for joint pricing and dispatch of ride-hailing platforms. In IEEE international conference on data mining, pages 61-70, 2019.
    [BibTeX] [Download PDF]
    @inproceedings{ICDM2019InBEDE,
    author = {Chen, Haipeng Chen and Jiao, Yan and Qin, Zhiwei and Tang, Xiaocheng and Li, Hao and An, Bo and Zhu, Hongtu and Ye, Jieping},
    title = {{InBEDE}: Integrating Contextual Bandit with {TD} Learning for Joint Pricing and Dispatch of Ride-Hailing Platforms},
    booktitle = { {IEEE} International Conference on Data Mining},
    pages = {61--70},
    year = {2019},
    url = {http://www.yelabs.net/publications/2019_icdm_InBEDE.pdf}
    }

  • John Holler, Risto Vuorio, Zhiwei Qin, Xiaocheng Tang, Yan Jiao, Tiancheng Jin, Satinder Singh, Chenxi Wang, and Jieping Ye. Deep reinforcement learning for multi-driver vehicle dispatching and repositioning problem. In IEEE international conference on data mining, pages 1090-1095, 2019.
    [BibTeX] [Download PDF]
    @inproceedings{ICDM2019DRL,
    author = {Holler, John and
    Vuorio, Risto and
    Qin, Zhiwei and
    Tang, Xiaocheng and
    Jiao, Yan and
    Jin, Tiancheng and
    Singh, Satinder and
    Wang, Chenxi and
    Ye, Jieping },
    title = {Deep Reinforcement Learning for Multi-driver Vehicle Dispatching and Repositioning Problem},
    booktitle = {{IEEE} International Conference on Data Mining},
    pages = {1090--1095},
    year = {2019},
    url = {http://www.yelabs.net/publications/2019_icdm_DRL.pdf}
    }

  • Lingyu Zhang, Tianshu Song, Yongxin Tong, Zimu Zhou, Dan Li, Wei Ai, Lulu Zhang, Guobin Wu, Yan Liu, and Jieping Ye. Recommendation-based team formation for on-demand taxi-calling platforms. In Proceedings of the 28th ACM international conference on information and knowledge management, pages 59-68, 2019.
    [BibTeX] [Download PDF]
    @inproceedings{CIKM2019team,
    author = {Zhang, Lingyu and
    Song, Tianshu and
    Tong, Yongxin and
    Zhou, Zimu and
    Li, Dan and
    Ai, Wei and
    Zhang, Lulu and
    Wu, Guobin and
    Liu, Yan and
    Ye, Jieping },
    title = {Recommendation-based Team Formation for On-demand Taxi-calling Platforms},
    booktitle = {Proceedings of the 28th {ACM} International Conference on Information and Knowledge Management},
    pages = {59--68},
    year = {2019},
    url = {http://www.yelabs.net/publications/2019_cikm_team.pdf}
    }

  • Jiarui Jin, Ming Zhou, Weinan Zhang, Minne Li, Zilong Guo, Zhiwei Qin, Yan Jiao, Xiaocheng Tang, Chenxi Wang, Jun Wang, Guobin Wu, and Jieping Ye. Coride: joint order dispatching and fleet management for multi-scale ride-hailing platforms. In Proceedings of the 28th ACM international conference on information and knowledge management, pages 1983-1992, 2019.
    [BibTeX] [Download PDF]
    @inproceedings{CIKM2019CoRide,
    author = {Jin, Jiarui and
    Zhou, Ming and
    Zhang, Weinan and
    Li, Minne and
    Guo, Zilong and
    Qin, Zhiwei and
    Jiao, Yan and
    Tang, Xiaocheng and
    Wang, Chenxi and
    Wang, Jun and
    Wu, Guobin and
    Ye, Jieping },
    title = {CoRide: Joint Order Dispatching and Fleet Management for Multi-Scale Ride-Hailing Platforms},
    booktitle = {Proceedings of the 28th {ACM} International Conference on Information and Knowledge Management},
    pages = {1983--1992},
    year = {2019},
    url = {http://www.yelabs.net/publications/2019_cikm_CoRide.pdf}
    }

  • Ming Zhou, Jiarui Jin, Weinan Zhang, Zhiwei Qin, Yan Jiao, Chenxi Wang, Guobin Wu, Yong Yu, and Jieping Ye. Multi-agent reinforcement learning for order-dispatching via order-vehicle distribution matching. In Proceedings of the 28th ACM international conference on information and knowledge management, pages 2645-2653, 2019.
    [BibTeX] [Download PDF]
    @inproceedings{CIKM2019MARL,
    author = {Zhou, Ming and
    Jin, Jiarui and
    Zhang, Weinan and
    Qin, Zhiwei and
    Jiao, Yan and
    Wang, Chenxi and
    Wu, Guobin and
    Yu, Yong and
    Ye, Jieping },
    title = {Multi-Agent Reinforcement Learning for Order-dispatching via Order-Vehicle Distribution Matching},
    booktitle = {Proceedings of the 28th {ACM} International Conference on Information and Knowledge Management},
    pages = {2645--2653},
    year = {2019},
    url = {http://www.yelabs.net/publications/2019_cikm_MARL.pdf}
    }

  • Xiaocheng Tang, Zhiwei Qin, Fan Zhang, Zhaodong Wang, Zhe Xu, Yintai Ma, Hongtu Zhu, and Jieping Ye. A deep value-network based approach for multi-driver order dispatching. In Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery and data mining, pages 1780-1790, 2019.
    [BibTeX] [Download PDF]
    @inproceedings{KDD2019VNet,
    author = {Tang, Xiaocheng and
    Qin, Zhiwei and
    Zhang, Fan and
    Wang, Zhaodong and
    Xu, Zhe and
    Ma, Yintai and
    Zhu, Hongtu and
    Ye, Jieping},
    title = {A Deep Value-network Based Approach for Multi-Driver Order Dispatching},
    booktitle = {Proceedings of the 25th {ACM} {SIGKDD} International Conference on Knowledge Discovery and Data Mining},
    pages = {1780--1790},
    year = {2019},
    url = {http://www.yelabs.net/publications/2019_kdd_vnet.pdf}
    }

  • Chunyi Liu, Peng Wang, Jiang Xu, Zang Li, and Jieping Ye. Automatic dialogue summary generation for customer service. In Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery and data mining, pages 1957-1965, 2019.
    [BibTeX] [Download PDF]
    @inproceedings{KDD2019CS,
    author = {Liu, Chunyi and
    Wang, Peng and
    Xu, Jiang and
    Li, Zang and
    Ye, Jieping},
    title = {Automatic Dialogue Summary Generation for Customer Service},
    booktitle = {Proceedings of the 25th {ACM} {SIGKDD} International Conference on Knowledge Discovery and Data Mining},
    pages = {1957--1965},
    year = {2019},
    url = {http://www.yelabs.net/publications/2019_kdd_CS.pdf}
    }

  • Wenjie Shang, Yang Yu, Qingyang Li, Zhiwei Qin, Yiping Meng, and Jieping Ye. Environment reconstruction with hidden confounders for reinforcement learning based recommendation. In Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery and data mining, pages 566-576, 2019.
    [BibTeX] [Download PDF]
    @inproceedings{KDD2019Counfounders,
    author = {Shang, Wenjie and
    Yu, Yang and
    Li, Qingyang and
    Qin, Zhiwei and
    Meng, Yiping and
    Ye, Jieping},
    title = {Environment Reconstruction with Hidden Confounders for Reinforcement Learning based Recommendation},
    booktitle = {Proceedings of the 25th {ACM} {SIGKDD} International Conference on
    Knowledge Discovery and Data Mining},
    pages = {566--576},
    year = {2019},
    url = {http://www.yelabs.net/publications/2019_kdd_confounders.pdf}
    }

  • Minne Li, Zhiwei Qin, Yan Jiao, Yaodong Yang, Jun Wang, Chenxi Wang, Guobin Wu, and Jieping Ye. Efficient ridesharing order dispatching with mean field multi-agent reinforcement learning. In Proceedings of the World Wide Web conference, pages 983-994, 2019.
    [BibTeX] [Download PDF]
    @inproceedings{MeanFWWW2019,
    author = {Li, Minne and
    Qin, Zhiwei and
    Jiao, Yan and
    Yang, Yaodong and
    Wang, Jun and
    Wang, Chenxi and
    Wu, Guobin and
    Ye, Jieping},
    title = {Efficient Ridesharing Order Dispatching with Mean Field Multi-Agent Reinforcement Learning},
    booktitle = {Proceedings of the {W}orld {W}ide {W}eb Conference},
    pages = {983--994},
    year = {2019},
    url = {https://doi.org/10.1145/3308558.3313433}
    }

  • Xu Geng, Yaguang Li, Leye Wang, Lingyu Zhang, Qiang Yang, Jieping Ye, and Yan Liu. Spatiotemporal multi-graph convolution network for ride-hailing demand forecasting. In Proceedings of the thirty-third AAAI conference on artificial intelligence, 2019.
    [BibTeX] [Download PDF]
    @inproceedings{AAAI2019demandpre,
    author = {Geng, Xu and
    Li, Yaguang and
    Wang, Leye and
    Zhang, Lingyu and
    Yang, Qiang and
    Ye, Jieping and
    Liu, Yan},
    title = {Spatiotemporal multi-graph convolution network for ride-hailing demand forecasting},
    booktitle = {Proceedings of the Thirty-Third {AAAI} Conference on Artificial Intelligence},
    pages = {},
    year = {2019},
    url = {http://www.yelabs.net/publications/2019_aaai_demandpre.pdf}
    }

  • Jie Wang, Zhanqiu Zhang, and Jieping Ye. Two-layer feature reduction for sparse-group Lasso via decomposition of convex sets. Journal of Machine Learning Research, 20(163):1-42, 2019.
    [BibTeX] [Download PDF]
    @article{JMLRTwoLayer2019,
    author = {Wang, Jie and Zhang, Zhanqiu and Ye, Jieping},
    title = {Two-Layer Feature Reduction for Sparse-Group {L}asso via Decomposition of Convex Sets},
    journal = {{Journal of Machine Learning Research}},
    year = {2019},
    volume = {20},
    number = {163},
    pages = {1-42},
    url = {http://jmlr.org/papers/v20/16-383.html}
    }

  • Jintao Ke, Hai Yang, Hongyu Zheng, Xiqun Chen, Yitian Jia, Pinghua Gong, and Jieping Ye. Hexagon-based convolutional neural network for supply-demand forecasting of ride-sourcing services. IEEE Transactions on Intelligent Transportation Systems, 20(11):4160-4173, 2019.
    [BibTeX] [Download PDF]
    @article{TITSHexagon2019,
    author = {Ke, Jintao and
    Yang, Hai and
    Zheng, Hongyu and
    Chen, Xiqun and
    Jia, Yitian and
    Gong, Pinghua and
    Ye, Jieping },
    title = {Hexagon-Based Convolutional Neural Network for Supply-Demand Forecasting of Ride-Sourcing Services},
    journal = {{IEEE Transactions on Intelligent Transportation Systems}},
    volume = {20},
    number = {11},
    pages = {4160--4173},
    year = {2019},
    url = {https://doi.org/10.1109/TITS.2018.2882861}
    }

  • Zhengxia Zou, Zhenwei Shi, Yuhong Guo, and Jieping Ye. Object detection in 20 years: a survey. CoRR, abs/1905.05055, 2019.
    [BibTeX] [Download PDF]
    @article{ODSurvey2019,
    author = {Zou, Zhengxia and
    Shi, Zhenwei and
    Guo, Yuhong and
    Ye, Jieping },
    title = {Object Detection in 20 Years: A Survey},
    journal = {{CoRR}},
    volume = {abs/1905.05055},
    year = {2019},
    url = {http://arxiv.org/abs/1905.05055}
    }

  • Zhengping Che, Guangyu Li, Tracy Li, Bo Jiang, Xuefeng Shi, Xinsheng Zhang, Ying Lu, Guobin Wu, Yan Liu, and Jieping Ye. D^2-City: A large-scale dashcam video dataset of diverse traffic scenarios. CoRR, abs/1904.01975, 2019.
    [BibTeX] [Download PDF]
    @article{D2City2019,
    author = {Che, Zhengping and
    Li, Guangyu and
    Li, Tracy and
    Jiang, Bo and
    Shi, Xuefeng and
    Zhang, Xinsheng and
    Lu, Ying and
    Wu, Guobin and
    Liu, Yan and
    Ye, Jieping },
    title = {{D^2}-{C}ity: {A} Large-Scale Dashcam Video Dataset of
    Diverse Traffic Scenarios},
    journal = {{CoRR}},
    volume = {abs/1904.01975},
    year = {2019},
    url = {http://arxiv.org/abs/1904.01975}
    }

2018

  • Zhaodong Wang, Zhiwei Qin, Xiaocheng Tang, Jieping Ye, and Hongtu Zhu. Deep reinforcement learning with knowledge transfer for online rides order dispatching. In IEEE international conference on data mining, pages 617-626, 2018.
    [BibTeX] [Download PDF]
    @inproceedings{ICDM2018DRLtransfer,
    author = {Wang, Zhaodong and
    Qin, Zhiwei and
    Tang, Xiaocheng and
    Ye, Jieping and
    Zhu, Hongtu},
    title = {Deep Reinforcement Learning with Knowledge Transfer for Online Rides Order Dispatching},
    booktitle = {{IEEE} International Conference on Data Mining},
    pages = {617--626},
    year = {2018},
    url = {http://www.yelabs.net/publications/2015_icdm_DRLtransfer.pdf}
    }

  • Yaguang Li, Kun Fu, Zheng Wang, Cyrus Shahabi, Jieping Ye, and Yan Liu. Multi-task representation learning for travel time estimation. In Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery and data mining, pages 1695-1704, 2018.
    [BibTeX] [Download PDF]
    @inproceedings{KDD2018MTLETA,
    author = {Li, Yaguang and
    Fu, Kun and
    Wang, Zheng and
    Shahabi, Cyrus and
    Ye, Jieping and
    Liu, Yan},
    title = {Multi-task Representation Learning for Travel Time Estimation},
    booktitle = {Proceedings of the 24th {ACM} {SIGKDD} International Conference on Knowledge Discovery and Data Mining},
    pages = {1695--1704},
    year = {2018},
    url = {http://www.yelabs.net/publications/2018_kdd_MTLETA.pdf}
    }

  • Zhe Xu, Zhixin Li, Qingwen Guan, Dingshui Zhang, Qiang Li, Junxiao Nan, Chunyang Liu, Wei Bian, and Jieping Ye. Large-scale order dispatch in on-demand ride-hailing platforms: A learning and planning approach. In Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery and data mining, pages 905-913, 2018.
    [BibTeX] [Download PDF]
    @inproceedings{KDD2018dispatch,
    author = {Xu, Zhe and
    Li, Zhixin and
    Guan, Qingwen and
    Zhang, Dingshui and
    Li, Qiang and
    Nan, Junxiao and
    Liu, Chunyang and
    Bian, Wei and
    Ye, Jieping},
    title = {Large-Scale Order Dispatch in On-Demand Ride-Hailing Platforms: {A} Learning and Planning Approach},
    booktitle = {Proceedings of the 24th {ACM} {SIGKDD} International Conference on Knowledge Discovery and Data Mining},
    pages = {905--913},
    year = {2018},
    url = {http://www.yelabs.net/publications/2018_kdd_dispatch.pdf}
    }

  • Zheng Wang, Kun Fu, and Jieping Ye. Learning to estimate the travel time. In Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery and data mining, pages 858-866, 2018.
    [BibTeX] [Download PDF]
    @inproceedings{KDD2018ETA,
    author = {Wang, Zheng and
    Fu, Kun and
    Ye, Jieping},
    title = {Learning to Estimate the Travel Time},
    booktitle = {Proceedings of the 24th {ACM} {SIGKDD} International Conference on
    Knowledge Discovery and Data Mining},
    pages = {858--866},
    year = {2018},
    url = {http://www.yelabs.net/publications/2018_kdd_ETA.pdf}
    }

  • Huaxiu Yao, Fei Wu, Jintao Ke, Xianfeng Tang, Yitian Jia, Siyu Lu, Pinghua Gong, Jieping Ye, and Zhenhui Li. Deep multi-view spatial-temporal network for taxi demand prediction. In Proceedings of the thirty-second AAAI conference on artificial intelligence, pages 2588-2595, 2018.
    [BibTeX] [Download PDF]
    @inproceedings{AAAI2018demandpre,
    author = {Yao, Huaxiu and
    Wu, Fei and
    Ke, Jintao and
    Tang, Xianfeng and
    Jia, Yitian and
    Lu, Siyu and
    Gong, Pinghua and
    Ye, Jieping and
    Li, Zhenhui},
    title = {Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction},
    booktitle = {Proceedings of the Thirty-Second {AAAI} Conference on Artificial Intelligence},
    pages = {2588--2595},
    year = {2018},
    url = {http://www.yelabs.net/publications/2018_aaai_demandpre.pdf}
    }

  • Shaogang Ren, Shuai Huang, Jieping Ye, and Xiaoning Qian. Safe feature screening for generalized LASSO. IEEE transactions on pattern analysis and machine intelligence, 40(12):2992-3006, 2018.
    [BibTeX] [Download PDF]
    @article{TPAMI2018_screening,
    author = {Ren, Shaogang and
    Huang, Shuai and
    Ye, Jieping and
    Qian, Xiaoning},
    title = {Safe Feature Screening for Generalized {LASSO}},
    journal = {{IEEE} Transactions on Pattern Analysis and Machine Intelligence},
    volume = {40},
    number = {12},
    pages = {2992--3006},
    year = {2018},
    url = {http://www.yelabs.net/publications/2018_tpami_screening.pdf}
    }

2017

  • Lingyu Zhang, Tao Hu, Yue Min, Guobin Wu, Junying Zhang, Pengcheng Feng, Pinghua Gong, and Jieping Ye. A taxi order dispatch model based on combinatorial optimization. In Proceedings of the 23rd ACM SIGKDD international conference on knowledge discovery and data mining, pages 2151-2159, 2017.
    [BibTeX] [Download PDF]
    @inproceedings{KDD2017_Dispatch,
    author = {Zhang, Lingyu and
    Hu, Tao and
    Min, Yue and
    Wu, Guobin and
    Zhang, Junying and
    Feng, Pengcheng and
    Gong, Pinghua and Ye, Jieping},
    title = {A Taxi Order Dispatch Model based On Combinatorial Optimization},
    booktitle = {Proceedings of the 23rd {ACM} {SIGKDD} International Conference on Knowledge Discovery and Data Mining},
    pages = {2151--2159},
    year = {2017},
    url = {http://www.yelabs.net/publications/2017_kdd_dispatch.pdf}
    }

  • Yongxin Tong, Yuqiang Chen, Zimu Zhou, Lei Chen, Jie Wang, Qiang Yang, Jieping Ye, and Weifeng Lv. The simpler the better: A unified approach to predicting original taxi demands based on large-scale online platforms. In Proceedings of the 23rd ACM SIGKDD international conference on knowledge discovery and data mining, pages 1653-1662, 2017.
    [BibTeX] [Download PDF]
    @inproceedings{KDD2017_DemandPre,
    author = {Tong, Yongxin and
    Chen, Yuqiang and
    Zhou, Zimu and
    Chen, Lei and
    Wang, Jie and
    Yang, Qiang and Ye, Jieping and Lv, Weifeng},
    title = {The Simpler The Better: {A} Unified Approach to Predicting Original Taxi Demands based on Large-Scale Online Platforms},
    booktitle = {Proceedings of the 23rd {ACM} {SIGKDD} International Conference on Knowledge Discovery and Data Mining},
    pages = {1653--1662},
    year = {2017},
    url = {http://www.yelabs.net/publications/2017_kdd_demandpre.pdf}
    }

  • Weizhong Zhang, Bin Hong, Wei Liu, Jieping Ye, Deng Cai, Xiaofei He, and Jie Wang. Scaling up sparse support vector machines by simultaneous feature and sample reduction. In Proceedings of the 34th international conference on machine learning, pages 4016-4025, 2017.
    [BibTeX] [Download PDF]
    @inproceedings{ICML2017_SSVM,
    author = {Zhang, Weizhong and
    Hong, Bin and
    Liu, Wei and
    Ye, Jieping and
    Cai, Deng and
    He, Xiaofei and
    Wang, Jie},
    title = {Scaling Up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction},
    booktitle = {Proceedings of the 34th International Conference on Machine Learning},
    pages = {4016--4025},
    year = {2017},
    url = {http://www.yelabs.net/publications/2017_icml_ssvm.pdf}
    }

  • Zhi Nie, Binbin Lin, Shuai Huang, Naren Ramakrishnan, Wei Fan, and Jieping Ye. Pruning decision trees via max-heap projection. In Proceedings of the 2017 SIAM international conference on data mining, pages 10-18, 2017.
    [BibTeX] [Download PDF]
    @inproceedings{SDM2017_treepruning,
    author = {Nie, Zhi and
    Lin, Binbin and
    Huang, Shuai and
    Ramakrishnan, Naren and
    Fan, Wei and
    Ye, Jieping},
    title = {Pruning Decision Trees via Max-Heap Projection},
    booktitle = {Proceedings of the 2017 {SIAM} International Conference on Data Mining},
    pages = {10--18},
    year = {2017},
    url = {http://www.yelabs.net/publications/2017_sdm_treepruning.pdf}
    }

  • Yongxin Tong, Libin Wang, Zimu Zhou, Bolin Ding, Lei Chen, Jieping Ye, and Ke Xu. Flexible online task assignment in real-time spatial data. PVLDB, 10(11):1334-1345, 2017.
    [BibTeX] [Download PDF]
    @article{PVLDB2017_Task,
    author = {Tong, Yongxin and
    Wang, Libin and
    Zhou, Zimu and
    Ding, Bolin and
    Chen, Lei and
    Ye, Jieping and
    Xu, Ke},
    title = {Flexible Online Task Assignment in Real-Time Spatial Data},
    journal = {{PVLDB}},
    volume = {10},
    number = {11},
    pages = {1334--1345},
    year = {2017},
    url = {http://www.yelabs.net/publications/2017_pvldb_task.pdf}
    }

2016

  • Ming Lin and Jieping Ye. A non-convex one-pass framework for generalized factorization machine and rank-one matrix sensing. In Advances in neural information processing systems, pages 1633-1641, 2016.
    [BibTeX] [Download PDF]
    @inproceedings{NIPS2016_gFM,
    author = {Lin, Ming and
    Ye, Jieping},
    title = {A Non-convex One-Pass Framework for Generalized Factorization Machine and Rank-One Matrix Sensing},
    booktitle = {Advances in Neural Information Processing Systems},
    pages = {1633--1641},
    year = {2016},
    url = {http://www.yelabs.net/publications/2016_nips_gFM.pdf}
    }

  • Liang Zhao, Jieping Ye, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. Hierarchical incomplete multi-source feature learning for spatiotemporal event forecasting. In Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining, pages 2085-2094, 2016.
    [BibTeX] [Download PDF]
    @inproceedings{KDD2016_HIMSFL,
    author = {Zhao, Liang and
    Ye, Jieping and
    Chen, Feng and
    Lu, Chang-Tien and
    Ramakrishnan, Naren},
    title = {Hierarchical Incomplete Multi-source Feature Learning for Spatiotemporal Event Forecasting},
    booktitle = {Proceedings of the 22nd {ACM} {SIGKDD} International Conference on Knowledge Discovery and Data Mining},
    pages = {2085--2094},
    year = {2016},
    url = {http://www.yelabs.net/publications/2016_kdd_HIMSFL.pdf}
    }

  • Tao Yang, Jun Liu, Pinghua Gong, Ruiwen Zhang, Xiaotong Shen, and Jieping Ye. Absolute Fused Lasso and its application to Genome-Wide Association Studies. In Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining, pages 1955-1964, 2016.
    [BibTeX] [Download PDF]
    @inproceedings{KDD2016_aFused,
    author = {Yang, Tao and
    Liu, Jun and
    Gong, Pinghua and
    Zhang, Ruiwen and
    Shen, Xiaotong and
    Ye, Jieping},
    title = {{A}bsolute {F}used {L}asso and Its Application to {G}enome-{W}ide {A}ssociation {S}tudies},
    booktitle = {Proceedings of the 22nd {ACM} {SIGKDD} International Conference on Knowledge Discovery and Data Mining},
    pages = {1955--1964},
    year = {2016},
    url = {http://www.yelabs.net/publications/2016_kdd_ aFused.pdf}
    }

  • Qingyang Li, Shuang Qiu, Shuiwang Ji, Paul M. Thompson, Jieping Ye, and Jie Wang. Parallel lasso screening for big data optimization. In Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining, pages 1705-1714, 2016.
    [BibTeX] [Download PDF]
    @inproceedings{KDD2016_Screening,
    author = {Li, Qingyang and
    Qiu, Shuang and
    Ji, Shuiwang and
    Thompson, Paul M. and
    Ye, Jieping and
    Wang, Jie},
    title = {Parallel Lasso Screening for Big Data Optimization},
    booktitle = {Proceedings of the 22nd {ACM} {SIGKDD} International Conference on Knowledge Discovery and Data Mining},
    pages = {1705--1714},
    year = {2016},
    url = {http://www.yelabs.net/publications/2016_kdd_screening.pdf}
    }

  • Yan Li, Jie Wang, Jieping Ye, and Chandan K. Reddy. A multi-task learning formulation for survival analysis. In Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining, pages 1715-1724, 2016.
    [BibTeX] [Download PDF]
    @inproceedings{KDD2016_survival,
    author = {Li, Yan and
    Wang, Jie and
    Ye, Jieping and
    Reddy, Chandan K.},
    title = {A Multi-Task Learning Formulation for Survival Analysis},
    booktitle = {Proceedings of the 22nd {ACM} {SIGKDD} International Conference on Knowledge Discovery and Data Mining},
    pages = {1715--1724},
    year = {2016},
    url = {http://www.yelabs.net/publications/2016_kdd_survival.pdf}
    }

  • Yashu Liu, Jie Wang, and Jieping Ye. An efficient algorithm for weak hierarchical Lasso. TKDD, 10(3):32:1–32:24, 2016.
    [BibTeX] [Download PDF]
    @article{TKDD2017_wHLasso,
    author = {Liu, Yashu and
    Wang, Jie and
    Ye, Jieping},
    title = {An Efficient Algorithm For Weak Hierarchical {L}asso},
    journal = {{TKDD}},
    volume = {10},
    number = {3},
    pages = {32:1--32:24},
    year = {2016},
    url = {http://www.yelabs.net/publications/2016_tkdd_wHLasso.pdf}
    }

2015

  • Jie Wang and Jieping Ye. Multi-layer feature reduction for tree structured group lasso via hierarchical projection. In Advances in Neural Information Processing Systems, 2015.
    [BibTeX] [Download PDF]
    @inproceedings{NIPS2015_tree,
    title = {Multi-Layer Feature Reduction for Tree Structured Group Lasso via Hierarchical Projection},
    author = {Wang, Jie and Ye, Jieping},
    booktitle = {{A}dvances in {N}eural {I}nformation {P}rocessing {S}ystems},
    pages = {},
    year = {2015},
    url = {http://www.yelabs.net/publications/2015_nips_tree.pdf}
    }

  • Pinghua Gong and Jieping Ye. HONOR: Hybrid Optimization for NOn-convex Regularized problems. In Advances in Neural Information Processing Systems, 2015.
    [BibTeX] [Download PDF]
    @inproceedings{NIPS2015_honor,
    title = {{HONOR}: {H}ybrid {O}ptimization for {NO}n-convex {R}egularized problems},
    author = {Gong, Pinghua and Ye, Jieping},
    booktitle = {{A}dvances in {N}eural {I}nformation {P}rocessing {S}ystems},
    pages = {},
    year = {2015},
    url = {http://www.yelabs.net/publications/2015_nips_honor.pdf}
    }

  • Wenlu Zhang, Rongjian Li, Tao Zeng, Qian Sun, Sudhir Kumar, Jieping Ye, and Shuiwang Ji. Deep model based transfer and multi-task learning for biological image analysis. In Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015.
    [BibTeX] [Download PDF]
    @inproceedings{zhang2015deep,
    title={Deep model based transfer and multi-task learning for biological image analysis},
    author={Zhang,Wenlu and Li, Rongjian and Zeng, Tao and Sun, Qian and Kumar, Sudhir and Ye, Jieping and Ji, Shuiwang},
    booktitle={{P}roceedings of the 21st {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={},
    year={2015},
    url = {http://www.yelabs.net/publications/2015_kdd_deep_mtl.pdf}
    }

  • Liang Zhao*, Qian Sun* (co-first author), Jieping Ye, Feng Chen, Chang-Tien Lu, and Naren Ramakrishnan. Multi-task learning for spatio-temporal event forecasting. In Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015.
    [BibTeX] [Download PDF]
    @inproceedings{Zhao2015multi,
    Title = {Multi-Task Learning for Spatio-Temporal Event Forecasting},
    Author = {Zhao*, Liang and Sun* (co-first author), Qian and Ye, Jieping and Chen, Feng and Lu, Chang-Tien and Ramakrishnan, Naren},
    booktitle={{P}roceedings of the 21st {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={},
    year={2015},
    url = {http://www.yelabs.net/publications/2015_kdd_event_detection.pdf}
    }

  • Qian Sun, Mohammad S. Amin, Baoshi Yan, Craig Martell, Vita Markman, Anmol Bhasin, and Jieping Ye. Transfer learning for bilingual content classification. In Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015.
    [BibTeX] [Download PDF]
    @inproceedings{Sun2015transfer,
    Title = {Transfer Learning for Bilingual Content Classification},
    Author = {Sun, Qian and Amin, Mohammad S. and Yan, Baoshi and Martell, Craig and Markman, Vita and Bhasin, Anmol and Ye, Jieping},
    booktitle={{P}roceedings of the 21st {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages = {},
    Year = {2015},
    url = {http://www.yelabs.net/publications/2015_kdd_transfer.pdf}
    }

  • Sen Yang, Qian Sun, Shuiwang Ji, Peter Wonka, Ian Davidson, and Jieping Ye. Structural graphical lasso for learning mouse brain connectivity. In Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015.
    [BibTeX] [Download PDF]
    @inproceedings{yang2015structural,
    Title = {Structural Graphical Lasso for Learning Mouse Brain Connectivity},
    Author = {Yang, Sen and Sun, Qian and Ji, Shuiwang and Wonka, Peter and Davidson, Ian and Ye, Jieping},
    booktitle={{P}roceedings of the 21st {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={},
    year={2015},
    url = {http://www.yelabs.net/publications/2015_kdd_structural.pdf}
    }

  • Zheng Wang, Prithwish Chakraborty, Sumiko Mekaru, John Brownstein, Jiepin Ye, and Naren Ramakrishnan. Dynamic poisson autoregression for influenza-like-illness case counts prediction. In Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015.
    [BibTeX] [Download PDF]
    @inproceedings{wang2015dynamic,
    Title = {Dynamic Poisson Autoregression for Influenza-Like-Illness Case Counts Prediction},
    Author = {Wang, Zheng and Chakraborty, Prithwish and Mekaru, Sumiko and Brownstein, John and Ye, Jiepin and Ramakrishnan, Naren},
    booktitle={{P}roceedings of the 21st {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={},
    year={2015},
    url = {http://www.yelabs.net/publications/2015_kdd_dynamic.pdf}
    }

  • Shayok Chakraborty, Vineeth Balasubramanian, Adepu Ravi Sankar, Sethuraman Panchanathan, and Jieping Ye. BatchRank: a novel batch mode active learning framework for hierarchical classification. In Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015.
    [BibTeX] [Download PDF]
    @inproceedings{Chakraborty2015batch,
    Title = {Batch{R}ank: A Novel Batch Mode Active Learning Framework for Hierarchical Classification},
    Author = {Chakraborty, Shayok and Balasubramanian, Vineeth and Ravi Sankar, Adepu and Panchanathan, Sethuraman and Ye, Jieping},
    booktitle={{P}roceedings of the 21st {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={},
    year={2015},
    url = {http://www.yelabs.net/publications/2015_kdd_batchrank.pdf}
    }

  • Jie Wang and Jieping Ye. Safe screening for multi-task feature learning with multiple data matrices. In Proceedings of the 32nd International Conference on Machine Learning, 2015.
    [BibTeX] [Download PDF]
    @inproceedings{wang2015safe,
    title={Safe Screening for Multi-Task Feature Learning with Multiple Data Matrices},
    author={Wang, Jie and Ye, Jieping},
    booktitle={{P}roceedings of the 32nd {I}nternational {C}onference on {M}achine {L}earning},
    pages={},
    year={2015},
    url = {http://www.yelabs.net/publications/2015-icml-MTFL-screening.pdf}
    }

  • Pinghua Gong and Jieping Ye. A modified orthant-wise limited memory quasi-newton method with convergence analysis. In Proceedings of the 32nd International Conference on Machine Learning, 2015.
    [BibTeX] [Download PDF]
    @inproceedings{gong2015modified,
    title={A Modified Orthant-Wise Limited Memory Quasi-Newton Method with Convergence Analysis},
    author={Gong, Pinghua and Ye, Jieping},
    booktitle={{P}roceedings of the 32nd {I}nternational {C}onference on {M}achine {L}earning},
    pages={},
    year={2015},
    url = {http://www.yelabs.net/publications/2015-icml-newOWL-QN.pdf}
    }

  • Tao Yang, Jie Wang, Qian Sun, Derrek Paul Hibar, Neda Jahanshad, Li Liu, Yalin Wang, Liang Zhan, Paul Thompson, and Jieping Ye. Detecting genetic risk factors for Alzheimer’s disease in whole genome sequence data via Lasso screening. In IEEE International Symposium on Biomedical Imaging, 2015.
    [BibTeX] [Download PDF]
    @InProceedings{yang2015detecting,
    Title = {Detecting Genetic Risk Factors for {A}lzheimer's Disease in Whole Genome Sequence Data via {L}asso Screening},
    Author = {Yang, Tao and Wang, Jie and Sun, Qian and Hibar, Derrek Paul and Jahanshad, Neda and Liu, Li and Wang, Yalin and Zhan, Liang and Thompson, Paul and Ye, Jieping},
    Booktitle = {{IEEE} {I}nternational {S}ymposium on {B}iomedical {I}maging},
    Year = {2015},
    url = {http://www.yelabs.net/publications/2015_isbi_detecting.pdf}
    }

  • Liang Zhan, Yashu Liu, Jiayu Zhou, Jieping Ye, and Paul Thompson. Boosting classification accuracy of diffusion MRI derived brain networks for the subtypes of Mild Cognitive Impairment using Higher Order Singular Value Decomposition. In IEEE International Symposium on Biomedical Imaging, 2015.
    [BibTeX] [Download PDF]
    @InProceedings{zhan2015boosting,
    Title = {Boosting Classification Accuracy of Diffusion {MRI} Derived Brain Networks for the Subtypes of {M}ild {C}ognitive {I}mpairment using {H}igher {O}rder {S}ingular {V}alue {D}ecomposition},
    Author = {Zhan, Liang and Liu, Yashu and Zhou, Jiayu and Ye, Jieping and Thompson, Paul},
    Booktitle = {{IEEE} {I}nternational {S}ymposium on {B}iomedical {I}maging},
    Year = {2015},
    url = {http://www.yelabs.net/publications/2015_isbi_dmri.pdf}
    }

  • Zhi Nie, Tao Yang, Yashu Liu, Binbin Lin, Qingyang Li, Vaibhav A. Narayan, Gayle Wittenbegr, and Jieping Ye. Melancholic depression prediction by identifying representative features in metabolic and microarray profiles with missing values. In Pacific Symposium on Biocomputing, volume 20, pages 455-466, 2015.
    [BibTeX] [Download PDF]
    @InProceedings{nie2015melancholic,
    Title = {MELANCHOLIC DEPRESSION PREDICTION BY IDENTIFYING REPRESENTATIVE FEATURES IN METABOLIC AND MICROARRAY PROFILES WITH MISSING VALUES},
    Author = {Nie, Zhi and Yang, Tao and Liu, Yashu and Lin, Binbin and Li, Qingyang and Narayan, Vaibhav A and Wittenbegr, Gayle and Ye, , Jieping},
    Booktitle = {{P}acific {S}ymposium on {B}iocomputing},
    Year = {2015},
    Pages = {455--466},
    Volume = {20},
    Url = {http://www.yelabs.net/publications/2015_psb_melancholic.pdf}
    }

  • Tao Yang, Xinlin Zhao, Binbin Lin, Tao Zeng, Shuiwang Ji, and Jieping Ye. Automated gene expression pattern annotation in the mouse brain. In Pacific Symposium on Biocomputing, volume 20, pages 144-155, 2015.
    [BibTeX] [Download PDF]
    @InProceedings{yang2015automated,
    Title = {AUTOMATED GENE EXPRESSION PATTERN ANNOTATION IN THE MOUSE BRAIN},
    Author = {Yang, Tao and Zhao, Xinlin and Lin, Binbin and Zeng, Tao and Ji, Shuiwang and Ye, Jieping},
    Booktitle = {{P}acific {S}ymposium on {B}iocomputing},
    Year = {2015},
    Pages = {144--155},
    Volume = {20},
    Url = {http://www.yelabs.net/publications/2015_psb_automated.pdf}
    }

  • Deepak Kadetotad and et al. Parallel architecture with resistive crosspoint array for dictionary learning acceleration. IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 5:194-204, 2015} Number = {2.
    [BibTeX] [Download PDF]
    @Article{Kadetotad2015Parallel,
    Title = {Parallel Architecture with Resistive Crosspoint Array for Dictionary Learning Acceleration},
    Author = {Kadetotad, Deepak and et al},
    Journal = {{IEEE} {J}ournal on {E}merging and {S}elected {T}opics in {C}ircuits and {S}ystems},
    Year = {2015}
    Number = {2},
    Pages = {194-204},
    Volume = {5},
    url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7116611}
    }

  • Shayok Chakraborty, Vineeth Nallure Balasubramanian, Qian Sun, Sethuraman Panchanathan, and Jieping Ye. Active batch selection via convex relaxations with guaranteed solution bounds. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37(10):1945-1958, 2015. doi:10.1109/TPAMI.2015.2389848
    [BibTeX] [Download PDF]
    @Article{chakraborty2015active,
    Title = {Active Batch Selection via Convex Relaxations with Guaranteed Solution Bounds},
    Author = {Chakraborty, Shayok and Nallure Balasubramanian, Vineeth and Sun, Qian and Panchanathan, Sethuraman and Ye, Jieping},
    Journal = {{IEEE} {T}ransactions on {P}attern {A}nalysis and {M}achine {I}ntelligence},
    Year = {2015},
    Number = {10},
    Pages = {1945-1958},
    Volume = {37},
    Doi = {10.1109/TPAMI.2015.2389848},
    ISSN = {0162-8828},
    Keywords = {Electronic mail;Equations;Manuals;Optimization;Redundancy;Uncertainty;Vectors;Batch Mode Active Learning;Optimization},
    Url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=7006697&url=http%3A%2F%2Fieeexplore.ieee.org%2Fstamp%2Fstamp.jsp%3Ftp%3D%26arnumber%3D7006697}
    }

  • Jie Wang, Wei Fan, and Jieping Ye. Fused lasso screening rules via the monotonicity of subdifferentials. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37(9):1806-1820, 2015. doi:10.1109/TPAMI.2014.2388203
    [BibTeX] [Download PDF]
    @Article{wang2015fused,
    Title = {Fused Lasso Screening Rules via the Monotonicity of Subdifferentials},
    Author = {Wang, Jie and Fan, Wei and Ye, Jieping},
    Journal = {{IEEE} {T}ransactions on {P}attern {A}nalysis and {M}achine {I}ntelligence},
    Year = {2015},
    Number = {9},
    Pages = {1806-1820},
    Volume = {37},
    Doi = {10.1109/TPAMI.2014.2388203},
    ISSN = {0162-8828},
    Keywords = {Computational efficiency;Computational modeling;Feature extraction;Optimization;Standards;Tuning;Vectors;Fused Lasso;Screening;`1 regularization},
    Url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7001682&sortType%3Dasc_p_Sequence%26filter%3DAND%28p_IS_Number%3A4359286%29%26rowsPerPage%3D100}
    }

  • Sen Yang, Zhaosong Lu, Xiaotong Shen, Peter Wonka, and Jieping Ye. Fused Multiple Graphical Lasso. SIAM Journal on Optimization, 25(2):916-943, 2015.
    [BibTeX] [Download PDF]
    @Article{yang2015fused,
    Title = {Fused {M}ultiple {G}raphical {L}asso},
    Author = {Yang, Sen and Lu, Zhaosong and Shen, Xiaotong and Wonka, Peter and Ye, Jieping},
    Journal = {{SIAM} {J}ournal on {O}ptimization},
    volume = {25},
    number = {2},
    pages = {916-943},
    Year = {2015},
    url = {http://epubs.siam.org/doi/abs/10.1137/130936397}
    }

  • Zheng Wang, Ming-Jun Lai, Zhaosong Lu, Wei Fan, Hasan Davulcu, and Jieping Ye. Orthogonal rank-one matrix pursuit for low rank matrix completion. SIAM Journal on Scientific Computing, 37(1):A488-A514, 2015.
    [BibTeX] [Download PDF]
    @Article{wang2015orthogonal,
    Title = {Orthogonal Rank-One Matrix Pursuit for Low Rank Matrix Completion},
    Author = {Wang, Zheng and Lai, Ming-Jun and Lu, Zhaosong and Fan, Wei and Davulcu, Hasan and Ye, Jieping},
    Journal = {{SIAM} {J}ournal on {S}cientific {C}omputing},
    volume = {37},
    number = {1},
    pages = {A488-A514},
    Year = {2015},
    url = {http://epubs.siam.org/doi/abs/10.1137/130934271}
    }

  • Jie Wang, Peter Wonka, and Jieping Ye. Lasso screening rules via dual polytope projection. Journal of Machine Learning Research, 16:1063-1101, 2015.
    [BibTeX] [Download PDF]
    @Article{wang2015lasso,
    Title = {Lasso Screening Rules via Dual Polytope Projection},
    Author = {Wang, Jie and Wonka, Peter and Ye, Jieping},
    Journal = {{J}ournal of {M}achine {L}earning {R}esearch},
    Year = {2015},
    volume = {16},
    pages = {1063-1101},
    url = {http://www.jmlr.org/papers/v16/wang15a.html}
    }

  • Qi Yan, Jieping Ye, and Xiaotong Shen. Simultaneous pursuit of sparseness and rank structures for matrix decomposition. Journal of Machine Learning Research, 16:47-75, 2015.
    [BibTeX] [Download PDF]
    @Article{qi2015simultaneous,
    Title = {Simultaneous pursuit of sparseness and rank structures for matrix decomposition},
    Author = {Yan, Qi and Ye, Jieping and Shen, Xiaotong},
    Journal = {{J}ournal of {M}achine {L}earning {R}esearch},
    Year = {2015},
    volume = {16},
    pages = {47-75},
    url = {http://www.jmlr.org/papers/volume16/yan15a/yan15a.pdf}
    }

  • Shuo Xiang, Xiaotong Shen, and Jieping Ye. Efficient nonconvex sparse group feature selection via continuous and discrete optimization. Artificial Intelligence, 224:28-50, 2015.
    [BibTeX] [Download PDF]
    @Article{xiang2015efficient,
    Title = {Efficient Nonconvex Sparse Group Feature Selection via Continuous and Discrete Optimization},
    Author = {Xiang, Shuo and Shen, Xiaotong and Ye, Jieping},
    Journal = {{A}rtificial {I}ntelligence},
    volume = {224},
    pages = {28-50},
    Year = {2015},
    url = {http://dx.doi.org/10.1016/j.artint.2015.02.008}
    }

  • Zheng Wang and Jieping Ye. Querying discriminative and representative samples for batch mode active learning. ACM Transactions on Knowledge Discovery from Data, 9(3):17:1-17:23, 2015.
    [BibTeX] [Download PDF]
    @Article{wang2015querying,
    Title = {Querying discriminative and representative samples for batch mode active learning},
    Author = {Wang, Zheng and Ye, Jieping},
    Journal = {{ACM} {T}ransactions on {K}nowledge {D}iscovery from {D}ata},
    Year = {2015},
    volume = {9},
    number = {3},
    pages = {17:1-17:23},
    url = {http://dl.acm.org/citation.cfm?id=2700408}
    }

  • Buyue Qian, Xiang Wang, Jieping Ye, and Ian Davidson. A reconstruction error based framework for multi-label and multi-view learning. IEEE Transactions on Knowledge and Data Engineering, 27(3):594-607, 2015.
    [BibTeX] [Download PDF]
    @article{qian2015Reconst,
    author = {Qian, Buyue and
    Wang, Xiang and
    Ye, Jieping and
    Davidson, Ian},
    title = {A Reconstruction Error Based Framework for Multi-Label and Multi-View
    Learning},
    journal = {{IEEE} {T}ransactions on {K}nowledge and {D}ata {E}ngineering},
    volume = {27},
    number = {3},
    pages = {594--607},
    year = {2015},
    url = {http://dx.doi.org/10.1109/TKDE.2014.2339860}
    }

  • Tao Zeng, Rongjian Li, Ravi Mukkamala, Jieping Ye, and Shuiwang Ji. Deep convolutional neural networks for annotating gene expression patterns in the mouse brain. BMC Bioinformatics, 16:147, 2015.
    [BibTeX] [Download PDF]
    @Article{zeng2015Deep,
    Title = {Deep Convolutional Neural Networks for Annotating Gene Expression Patterns in the Mouse Brain},
    Author = {Zeng, Tao and Li, Rongjian and Mukkamala, Ravi and Ye, Jieping and Ji, Shuiwang},
    Journal = {{BMC} {B}ioinformatics},
    volume = {16},
    pages = {147},
    Year = {2015},
    url = {http://www.biomedcentral.com/1471-2105/16/147/abstract}
    }

  • Liang Zhan, Jiayu Zhou, Yalin Wang, Yan Jin, Neda Jahanshad, Gautam Prasad, Talia M. Nir, Cassandra D. Leonardo, Jieping Ye, and Paul M. Thompson. Comparison of 9 tractography algorithms for detecting abnormal structural brain networks in Alzheimer’s disease. Frontiers in Aging Neuroscience, 2015.
    [BibTeX] [Download PDF]
    @Article{zhan2015Comparison,
    Title = {Comparison of 9 Tractography Algorithms for Detecting Abnormal Structural Brain Networks in {A}lzheimer’s Disease},
    Author = {Zhan, Liang and Zhou, Jiayu and Wang, Yalin and Jin, Yan and Jahanshad, Neda and Prasad, Gautam and Nir, Talia M. and Leonardo, Cassandra D. and Ye, Jieping and Thompson, Paul M.},
    Journal = {{F}rontiers in {A}ging {N}euroscience},
    Year = {2015},
    url = {http://journal.frontiersin.org/article/10.3389/fnagi.2015.00048/abstract}
    }

  • Jinglei Lv and et al. Holistic atlases of functional networks and interactions reveal reciprocal organizational architecture of cortical function. IEEE Transactions on Biomedical Engineering, 62(4):1120-1231, 2015.
    [BibTeX] [Download PDF]
    @Article{Lv2015Holistic,
    Title = {Holistic Atlases of Functional Networks and Interactions Reveal Reciprocal Organizational Architecture of Cortical Function},
    Author = {Lv, Jinglei and et al},
    Journal = {{IEEE} {T}ransactions on {B}iomedical {E}ngineering},
    Year = {2015},
    volume = {62},
    number = {4},
    pages = {1120-1231},
    url = {http://www.ncbi.nlm.nih.gov/pubmed/25420254}
    }

  • Moo K. Chung, Jamie L. Hanson, Jieping Ye, Richard J. Davidson, and Seth D. Pollak. Persistent homology in sparse regression and its application to brain morphometry. IEEE Transactions on Medical Imaging, 34(9):1928-1939, 2015.
    [BibTeX] [Download PDF]
    @Article{Chung2015Persistent,
    Title = {Persistent Homology in Sparse Regression and Its Application to Brain Morphometry},
    Author = {Chung, Moo K. and Hanson, Jamie L. and Ye, Jieping and Davidson, Richard J. and Pollak, Seth D.},
    Journal = {{IEEE} {T}ransactions on {Medical} {I}maging},
    Year = {2015},
    volume = {34},
    number = {9},
    pages = {1928-1939},
    year = {2015},
    url = {http://arxiv.org/abs/1409.0177}
    }

2014

  • Jie Wang and Jieping Ye. Two-layer feature reduction for sparse-group lasso via decomposition of convex sets. In Advances in Neural Information Processing Systems, pages 2132-2140, 2014.
    [BibTeX] [Download PDF]
    @inproceedings{wang2014two,
    title={Two-Layer Feature Reduction for Sparse-Group Lasso via Decomposition of Convex Sets},
    author={Wang, Jie and Ye, Jieping},
    booktitle={{A}dvances in {N}eural {I}nformation {P}rocessing {S}ystems},
    pages={2132--2140},
    year={2014},
    url={http://www.yelabs.net/publications/2014_nips_twolayer.pdf}
    }

  • Jie Wang, Jiayu Zhou, Jun Liu, Peter Wonka, and Jieping Ye. A safe screening rule for sparse logistic regression. In Advances in Neural Information Processing Systems, pages 1053-1061. , 2014.
    [BibTeX] [Download PDF]
    @incollection{NIPS2014_5294,
    title = {A Safe Screening Rule for Sparse Logistic Regression},
    author = {Wang, Jie and Zhou, Jiayu and Liu, Jun and Wonka, Peter and Ye, Jieping},
    booktitle = {{A}dvances in {N}eural {I}nformation {P}rocessing {S}ystems},
    pages = {1053--1061},
    year = {2014},
    url = {http://www.yelabs.net/publications/2014_nips_screening.pdf}
    }

  • Yashu Liu, Jie Wang, and Jieping Ye. An efficient algorithm for weak hierarchical lasso. In Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 283-292, 2014.
    [BibTeX] [Download PDF]
    @inproceedings{liu2014efficient,
    title={An efficient algorithm for weak hierarchical lasso},
    author={Liu, Yashu and Wang, Jie and Ye, Jieping},
    booktitle={{P}roceedings of the 20th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={283--292},
    year={2014},
    url = {http://www.yelabs.net/publications/2014_kdd_weakhierarchical.pdf}
    }

  • Jiayu Zhou, Fei Wang, Jianying Hu, and Jieping Ye. From micro to macro: data driven phenotyping by densification of longitudinal electronic medical records. In Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 135-144, 2014.
    [BibTeX] [Download PDF]
    @inproceedings{zhou2014micro,
    title={From micro to macro: Data driven phenotyping by densification of longitudinal electronic medical records},
    author={Zhou, Jiayu and Wang, Fei and Hu, Jianying and Ye, Jieping},
    booktitle={{P}roceedings of the 20th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={135--144},
    year={2014},
    url = {http://www.yelabs.net/publications/2014_kdd_longitudinal.pdf}
    }

  • Pinghua Gong, Jiayu Zhou, Wei Fan, and Jieping Ye. Efficient multi-task feature learning with calibration. In Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 761-770, 2014.
    [BibTeX] [Download PDF]
    @inproceedings{gong2014efficient,
    title={Efficient multi-task feature learning with calibration},
    author={Gong, Pinghua and Zhou, Jiayu and Fan, Wei and Ye, Jieping},
    booktitle={{P}roceedings of the 20th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={761--770},
    year={2014},
    url = {http://www.yelabs.net/publications/2014_kdd_efficientmultitask.pdf}
    }

  • Shuo Xiang, Tao Yang, and Jieping Ye. Simultaneous feature and feature group selection through hard thresholding. In Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 532-541, 2014.
    [BibTeX] [Download PDF]
    @inproceedings{xiang2014simultaneous,
    title={Simultaneous feature and feature group selection through hard thresholding},
    author={Xiang, Shuo and Yang, Tao and Ye, Jieping},
    booktitle={{P}roceedings of the 20th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={532--541},
    year={2014},
    url = {http://www.yelabs.net/publications/2014_kdd_simultaneousselection.pdf}
    }

  • Jie Wang, Peter Wonka, and Jieping Ye. Scaling svm and least absolute deviations via exact data reduction. In Proceedings of the 31st International Conference on Machine Learning, 2014.
    [BibTeX] [Download PDF]
    @InProceedings{wang2013scaling,
    Title = {Scaling svm and least absolute deviations via exact data reduction},
    Author = {Wang, Jie and Wonka, Peter and Ye, Jieping},
    Booktitle = {{P}roceedings of the 31st {I}nternational {C}onference on {M}achine {L}earning},
    Year = {2014},
    url = {http://www.yelabs.net/publications/2014_icml_scalingsvm.pdf}
    }

  • Zheng Wang, Ming-Jun Lai, Zhaosong Lu, Wei Fan, Hasan Davulcu, and Jieping Ye. Rank-one matrix pursuit for matrix completion. In Proceedings of the 31st International Conference on Machine Learning, pages 91-99, 2014.
    [BibTeX] [Download PDF]
    @inproceedings{wang2014rank,
    title={Rank-One Matrix Pursuit for Matrix Completion},
    author={Wang, Zheng and Lai, Ming-Jun and Lu, Zhaosong and Fan, Wei and Davulcu, Hasan and Ye, Jieping},
    booktitle={{P}roceedings of the 31st {I}nternational {C}onference on {M}achine {L}earning},
    pages={91--99},
    year={2014},
    url = {http://www.yelabs.net/publications/2014_icml_rankonematrixpursuit.pdf}
    }

  • Binbin Lin, Ji Yang, Xiaofei He, and Jieping Ye. Geodesic distance function learning via heat flows on vector fields. In Proceedings of the 31st International Conference on Machine Learning, 2014.
    [BibTeX] [Download PDF]
    @InProceedings{lin2014geodesic,
    Title = {Geodesic distance function learning via heat flows on vector fields},
    Author = {Lin, Binbin and Yang, Ji and He, Xiaofei and Ye, Jieping},
    Booktitle = {{P}roceedings of the 31st {I}nternational {C}onference on {M}achine {L}earning},
    Year = {2014},
    url = {http://www.yelabs.net/publications/2014_icml_geodesicdistance.pdf}
    }

  • Jie Wang, Qingyang Li, Sen Yang, Wei Fan, Peter Wonka, and Jieping Ye. A highly scalable parallel algorithm for isotropic total variation models. In Proceedings of the 31st International Conference on Machine Learning, pages 235-243, 2014.
    [BibTeX] [Download PDF]
    @inproceedings{wang2014highly,
    title={A Highly Scalable Parallel Algorithm for Isotropic Total Variation Models},
    author={Wang, Jie and Li, Qingyang and Yang, Sen and Fan, Wei and Wonka, Peter and Ye, Jieping},
    booktitle={{P}roceedings of the 31st {I}nternational {C}onference on {M}achine {L}earning},
    pages={235--243},
    year={2014},
    url = {http://www.yelabs.net/publications/2014_icml_isotropictotalvariation.pdf}
    }

  • Jun Liu, Zheng Zhao, Zheng Wang, Jie Wang, and Jieping Ye. Safe screening with variational inequalities and its application to lasso. In Proceedings of the 31st International Conference on Machine Learning, 2014.
    [BibTeX] [Download PDF]
    @InProceedings{liu2013safe,
    Title = {Safe Screening With Variational Inequalities and Its Application to LASSO},
    Author = {Liu, Jun and Zhao, Zheng and Wang, Zheng and Wang, Jie and Ye, Jieping},
    Booktitle = {{P}roceedings of the 31st {I}nternational {C}onference on {M}achine {L}earning},
    Year = {2014},
    url = {http://www.yelabs.net/publications/2014_icml_safescreening.pdf}
    }

  • Ji Liu, Ryohei Fujimaki, and Jieping Ye. Forward-backward greedy algorithms for general convex smooth functions over a cardinality constraint. In Proceedings of the 31st International Conference on Machine Learning, 2014.
    [BibTeX] [Download PDF]
    @InProceedings{liu2013forward,
    Title = {Forward-backward greedy algorithms for general convex smooth functions over a cardinality constraint},
    Author = {Liu, Ji and Fujimaki, Ryohei and Ye, Jieping},
    Booktitle = {{P}roceedings of the 31st {I}nternational {C}onference on {M}achine {L}earning},
    Year = {2014},
    url = {http://www.yelabs.net/publications/2014_icml_forwardbackward.pdf}
    }

  • Yashu Liu, Zhi Nie, Jiayu Zhou, Michael Farnum, Vaibhav A. Narayan, Gayle Wittenberg, and Jieping Ye. Sparse generalized functional linear model for predicting remission status of depression patients. In Pacific Symposium on Biocomputing, volume 19, pages 364-375, 2013.
    [BibTeX] [Download PDF]
    @inproceedings{liu2013sparse,
    title={SPARSE GENERALIZED FUNCTIONAL LINEAR MODEL FOR PREDICTING REMISSION STATUS OF DEPRESSION PATIENTS},
    author={Liu, Yashu and Nie, Zhi and Zhou, Jiayu and Farnum, Michael and Narayan, Vaibhav A and Wittenberg, Gayle and Ye, Jieping},
    booktitle={{P}acific {S}ymposium on {B}iocomputing},
    volume={19},
    pages={364--375},
    year={2013},
    url = {http://www.yelabs.net/publications/2014_psb_sparsegeneralized.pdf}
    }

  • Ivan Montiel, Charlotte Konikoff, Bremen Braun, Mary Packard, Sian L. Gramates, Qian Sun, Jieping Ye, and Sudhir Kumar. MyFX: a turn-key software for laboratory desktops to analyze spatial patterns of gene expression in Drosophila embryos. Bioinformatics, 30(9):1319-1321, 2014. doi:10.1093/bioinformatics/btu007
    [BibTeX] [Download PDF]
    @article{montiel2014myfx,
    author = {Montiel, Ivan and Konikoff, Charlotte and Braun, Bremen and Packard, Mary and Gramates, Sian L. and Sun, Qian and Ye, Jieping and Kumar, Sudhir},
    title = {my{FX}: a turn-key software for laboratory desktops to analyze spatial patterns of gene expression in {D}rosophila embryos},
    volume = {30},
    number = {9},
    pages = {1319-1321},
    year = {2014},
    doi = {10.1093/bioinformatics/btu007},
    URL = {http://bioinformatics.oxfordjournals.org/content/30/9/1319.abstract},
    eprint = {http://bioinformatics.oxfordjournals.org/content/30/9/1319.full.pdf+html},
    journal = {Bioinformatics}
    }

  • Lei Yuan, Cheng Pan, Shuiwang Ji, Michael McCutchan, Zhi-Hua Zhou, Stuart J. Newfeld, Sudhir Kumar, and Jieping Ye. Automated annotation of developmental stages of Drosophila embryos in images containing spatial patterns of expression. Bioinformatics, 30(2):266-273, 2014. doi:10.1093/bioinformatics/btt648
    [BibTeX] [Download PDF]
    @article{yuan2014automated,
    author = {Yuan, Lei and Pan, Cheng and Ji, Shuiwang and McCutchan, Michael and Zhou, Zhi-Hua and Newfeld, Stuart J. and Kumar, Sudhir and Ye, Jieping},
    title = {Automated annotation of developmental stages of {D}rosophila embryos in images containing spatial patterns of expression},
    volume = {30},
    number = {2},
    pages = {266-273},
    year = {2014},
    doi = {10.1093/bioinformatics/btt648},
    URL = {http://bioinformatics.oxfordjournals.org/content/30/2/266.abstract},
    eprint = {http://bioinformatics.oxfordjournals.org/content/30/2/266.full.pdf+html},
    journal = {Bioinformatics}
    }

  • Shuo Xiang, Lei Yuan, Wei Fan, Yalin Wang, Paul M. Thompson, and Jieping Ye. Bi-level multi-source learning for heterogeneous block-wise missing data. Neuroimage, 102, Part 1:192-206, 2014. doi:http://dx.doi.org/10.1016/j.neuroimage.2013.08.015
    [BibTeX] [Download PDF]
    @article{xiang2014bi,
    title={Bi-level multi-source learning for heterogeneous block-wise missing data},
    author={Xiang, Shuo and Yuan, Lei and Fan, Wei and Wang, Yalin and Thompson, Paul M and Ye, Jieping},
    journal = {NeuroImage},
    volume = {102, Part 1},
    number = {0},
    pages = {192-206},
    year = {2014},
    publisher={Elsevier},
    issn = {1053-8119},
    doi = {http://dx.doi.org/10.1016/j.neuroimage.2013.08.015},
    url = {http://www.sciencedirect.com/science/article/pii/S1053811913008690},
    }

  • Rashmi Dubey, Jiayu Zhou, Yalin Wang, Paul M. Thompson, and Jieping Ye. Analysis of sampling techniques for imbalanced data: an n= 648 ADNI study. Neuroimage, 87:220-241, 2014. doi:http://dx.doi.org/10.1016/j.neuroimage.2013.10.005
    [BibTeX] [Download PDF]
    @article{dubey2014analysis,
    title={Analysis of sampling techniques for imbalanced data: An n= 648 {ADNI} study},
    author={Dubey, Rashmi and Zhou, Jiayu and Wang, Yalin and Thompson, Paul M and Ye, Jieping},
    journal={{N}euroImage},
    volume={87},
    pages={220--241},
    year={2014},
    publisher={Elsevier},
    issn = {1053-8119},
    doi = {http://dx.doi.org/10.1016/j.neuroimage.2013.10.005},
    url = {http://www.sciencedirect.com/science/article/pii/S1053811913010161}
    }

2013

  • Jie Wang, Jiayu Zhou, Peter Wonka, and Jieping Ye. Lasso screening rules via dual polytope projection. In Advances in Neural Information Processing Systems, pages 1070-1078, 2013.
    [BibTeX] [Download PDF]
    @INPROCEEDINGS{wang2013lasso,
    author = {Wang, Jie and Zhou, Jiayu and Wonka, Peter and Ye, Jieping},
    title = {Lasso screening rules via dual polytope projection},
    booktitle = {{A}dvances in {N}eural {I}nformation {P}rocessing {S}ystems},
    year = {2013},
    pages = {1070--1078},
    url = {http://www.yelab.net/publications/2013_NIPS_LassoScreening.pdf}
    }

  • Zheng Wang and Jieping Ye. Querying discriminative and representative samples for batch mode active learning. In Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 158-166, 2013.
    [BibTeX] [Download PDF]
    @INPROCEEDINGS{wang2013querying,
    author = {Wang, Zheng and Ye, Jieping},
    title = {Querying discriminative and representative samples for batch mode active learning},
    booktitle = {{P}roceedings of the 19th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    year = {2013},
    pages = {158--166},
    url = {http://www.yelab.net/publications/2013_KDD_Querying.pdf}
    }

  • Shuo Xiang, Lei Yuan, Wei Fan, Yalin Wang, Paul M. Thompson, and Jieping Ye. Multi-source learning with block-wise missing data for alzheimer’s disease prediction. In Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 185-193, 2013.
    [BibTeX] [Download PDF]
    @INPROCEEDINGS{xiang2013multi,
    author = {Xiang, Shuo and Yuan, Lei and Fan, Wei and Wang, Yalin and Thompson, Paul M and Ye, Jieping},
    title = {Multi-source learning with block-wise missing data for Alzheimer's disease prediction},
    booktitle = {{P}roceedings of the 19th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    year = {2013},
    pages = {185--193},
    url = {http://www.yelab.net/publications/2013_KDD_MultiSource.pdf}
    }

  • Qian Sun, Shuo Xiang, and Jieping Ye. Robust principal component analysis via capped norms. In Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 311-319, 2013.
    [BibTeX] [Download PDF]
    @INPROCEEDINGS{sun2013robust,
    author = {Sun, Qian and Xiang, Shuo and Ye, Jieping},
    title = {Robust principal component analysis via capped norms},
    booktitle = {{P}roceedings of the 19th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    year = {2013},
    pages = {311--319},
    url = {http://www.yelab.net/publications/2013_KDD_RobustPCA.pdf}
    }

  • Sen Yang, Jie Wang, Wei Fan, Xiatian Zhang, Peter Wonka, and Jieping Ye. An efficient ADMM algorithm for multidimensional anisotropic total variation regularization problems. In Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 641-649, 2013.
    [BibTeX] [Download PDF]
    @INPROCEEDINGS{yang2013efficient,
    author = {Yang, Sen and Wang, Jie and Fan, Wei and Zhang, Xiatian and Wonka, Peter and Ye, Jieping},
    title = {An efficient {ADMM} algorithm for multidimensional anisotropic total variation regularization problems},
    booktitle = {{P}roceedings of the 19th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    year = {2013},
    pages = {641--649},
    url = {http://www.yelab.net/publications/2013_KDD_TVReg.pdf}
    }

  • Jiayu Zhou, Zhaosong Lu, Jimeng Sun, Lei Yuan, Fei Wang, and Jieping Ye. Feafiner: biomarker identification from medical data through feature generalization and selection. In Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 1034-1042, 2013.
    [BibTeX] [Download PDF]
    @INPROCEEDINGS{zhou2013feafiner,
    author = {Zhou, Jiayu and Lu, Zhaosong and Sun, Jimeng and Yuan, Lei and Wang, Fei and Ye, Jieping},
    title = {FeaFiner: biomarker identification from medical data through feature generalization and selection},
    booktitle = {{P}roceedings of the 19th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    year = {2013},
    pages = {1034--1042},
    url = {http://www.yelab.net/publications/2013_KDD_FeaFiner.pdf}
    }

  • Ji Liu, Lei Yuan, and Jieping Ye. Guaranteed sparse recovery under linear transformation. In Proceedings of the 30th International Conference on Machine Learning, pages 91-99, 2013.
    [BibTeX] [Download PDF]
    @INPROCEEDINGS{liu2013guaranteed,
    author = {Liu, Ji and Yuan, Lei and Ye, Jieping},
    title = {Guaranteed Sparse Recovery under Linear Transformation},
    booktitle = {{P}roceedings of the 30th {I}nternational {C}onference on {M}achine {L}earning},
    year = {2013},
    pages = {91--99},
    url = {http://www.yelab.net/publications/2013_ICML_dictionarylasso.pdf}
    }

  • Pinghua Gong, Changshui Zhang, Zhaosong Lu, Jianhua Huang, and Jieping Ye. A general iterative shrinkage and thresholding algorithm for non-convex regularized optimization problems. In Proceedings of the 30th International Conference on Machine Learning, pages 37-45, 2013.
    [BibTeX] [Download PDF]
    @INPROCEEDINGS{gong2013general,
    author = {Gong, Pinghua and Zhang, Changshui and Lu, Zhaosong and Huang, Jianhua and Ye, Jieping},
    title = {A General Iterative Shrinkage and Thresholding Algorithm for Non-convex Regularized Optimization Problems},
    booktitle = {{P}roceedings of the 30th {I}nternational {C}onference on {M}achine {L}earning},
    year = {2013},
    pages = {37--45},
    url = {http://www.yelab.net/publications/2013_ICML_GIST.pdf}
    }

  • Shuo Xiang, Xiaoshen Tong, and Jieping Ye. Efficient sparse group feature selection via nonconvex optimization. In Proceedings of the 30th International Conference on Machine Learning, pages 284-292, 2013.
    [BibTeX] [Download PDF]
    @INPROCEEDINGS{xiang2013efficient,
    author = {Xiang, Shuo and Tong, Xiaoshen and Ye, Jieping},
    title = {Efficient Sparse Group Feature Selection via Nonconvex Optimization},
    booktitle = {{P}roceedings of the 30th {I}nternational {C}onference on {M}achine {L}earning},
    year = {2013},
    pages = {284--292},
    url = {http://www.yelab.net/publications/2013_ICML_SGLnonconvex.pdf}
    }

  • Rita Chattopadhyay, Wei Fan, Ian Davidson, Sethuraman Panchanathan, and Jieping Ye. Joint transfer and batch-mode active learning. In Proceedings of the 30th International Conference on Machine Learning, pages 253-261, 2013.
    [BibTeX] [Download PDF]
    @INPROCEEDINGS{chattopadhyay2013joint,
    author = {Chattopadhyay, Rita and Fan, Wei and Davidson, Ian and Panchanathan, Sethuraman and Ye, Jieping},
    title = {Joint transfer and batch-mode active learning},
    booktitle = {{P}roceedings of the 30th {I}nternational {C}onference on {M}achine {L}earning },
    year = {2013},
    pages = {253--261},
    url = {http://www.yelab.net/publications/2013_ICML_transfer.pdf}
    }

  • Shayok Chakraborty, Jiayu Zhou, Vineeth Balasubramanian, Sethuraman Panchanathan, Ian Davidson, and Jieping Ye. Active matrix completion. In Proceedings of the 13th International Conference on Data Mining, pages 81-90, 2013.
    [BibTeX] [Download PDF]
    @INPROCEEDINGS{chakraborty2013active,
    author = {Chakraborty, Shayok and Zhou, Jiayu and Balasubramanian, Vineeth and Panchanathan, Sethuraman and Davidson, Ian and Ye, Jieping},
    title = {Active Matrix Completion},
    booktitle = {{P}roceedings of the 13th {I}nternational {C}onference on {D}ata {M}ining},
    year = {2013},
    pages = {81--90},
    url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6729492}
    }

  • Jiayu Zhou, Jimeng Sun, Yashu Liu, Jianying Hu, and Jieping Ye. Patient risk prediction model via top-k stability selection. In Proceedings of the 13th Siam Conference on Data Mining, pages 55-63, 2013.
    [BibTeX] [Download PDF]
    @INPROCEEDINGS{zhou2013patient,
    author = {Zhou, Jiayu and Sun, Jimeng and Liu, Yashu and Hu, Jianying and Ye, Jieping},
    title = {Patient risk prediction model via top-k stability selection},
    booktitle = {{P}roceedings of the 13th {S}IAM {C}onference on {D}ata {M}ining},
    year = {2013},
    pages = {55--63},
    url = {http://www.yelab.net/publications/2013_SDM_riskprediction.pdf}
    }

  • Xiang Wang, Buyue Qian, Jieping Ye, and Ian Davidson. Multi-objective multi-view spectral clustering via pareto optimization. In Proceedings of the 13th Siam Conference on Data Mining, pages 234-242, 2013.
    [BibTeX] [Download PDF]
    @INPROCEEDINGS{wang2013multi,
    author = {Wang, Xiang and Qian, Buyue and Ye, Jieping and Davidson, Ian},
    title = {Multi-objective multi-view spectral clustering via pareto optimization},
    booktitle = {{P}roceedings of the 13th {S}IAM {C}onference on {D}ata {M}ining},
    year = {2013},
    pages = {234--242},
    url = {http://www.yelab.net/publications/2013_SDM_multiobj.pdf}
    }

  • Pinghua Gong, Jieping Ye, and Changshui Zhang. Multi-stage multi-task feature learning. Journal of Machine Learning Research, 14(1):2979-3010, 2013.
    [BibTeX] [Download PDF]
    @ARTICLE{gong2013multi,
    author = {Gong, Pinghua and Ye, Jieping and Zhang, Changshui},
    title = {Multi-stage multi-task feature learning},
    journal = {{J}ournal of {M}achine {L}earning {R}esearch},
    year = {2013},
    volume = {14},
    pages = {2979--3010},
    number = {1},
    url = {http://www.jmlr.org/papers/volume14/gong13a/gong13a.pdf}
    }

  • Jiayu Zhou, Jun Liu, Vaibhav A. Narayan, and Jieping Ye. Modeling disease progression via multi-task learning. NeuroImage, 78:233-248, 2013. doi:10.1016/j.neuroimage.2013.03.073
    [BibTeX] [Download PDF]
    @ARTICLE{zhou2013modeling,
    author = {Zhou, Jiayu and Liu, Jun and Narayan, Vaibhav A and Ye, Jieping},
    title = {Modeling disease progression via multi-task learning},
    journal = {{N}euro{I}mage},
    year = {2013},
    volume = {78},
    pages = {233--248},
    publisher = {Elsevier},
    doi = {10.1016/j.neuroimage.2013.03.073},
    url = {http://www.sciencedirect.com/science/article/pii/S1053811913003261}
    }

  • Qian Sun, Sherin Muckatira, Lei Yuan, Shuiwang Ji, Stuart Newfeld, Sudhir Kumar, and Jieping Ye. Image-level and group-level models for Drosophila gene expression pattern annotation. BMC Bioinformatics, 14(350), 2013. doi:10.1186/1471-2105-14-350
    [BibTeX] [Download PDF]
    @ARTICLE{sun2013image,
    author = {Sun, Qian and Muckatira, Sherin and Yuan, Lei and Ji, Shuiwang and Newfeld, Stuart and Kumar, Sudhir and Ye, Jieping},
    title = {Image-level and group-level models for {D}rosophila gene expression pattern annotation},
    journal = {{BMC} {B}ioinformatics},
    year = {2013},
    volume = {14},
    number = {350},
    publisher = {BioMed Central Ltd},
    doi = {10.1186/1471-2105-14-350},
    url = {http://www.biomedcentral.com/1471-2105/14/350}
    }

  • Lei Yuan, Jun Liu, and Jieping Ye. Efficient methods for overlapping group Lasso. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(9):2104-2116, 2013. doi:10.1109/TPAMI.2013.17
    [BibTeX] [Download PDF]
    @ARTICLE{yuan2013efficient,
    author = {Yuan, Lei and Liu, Jun and Ye, Jieping},
    title = {Efficient Methods for Overlapping Group {L}asso},
    journal = {{IEEE} {T}ransactions on {P}attern {A}nalysis and {M}achine {I}ntelligence},
    year = {2013},
    volume = {35},
    pages = {2104--2116},
    number = {9},
    publisher = {IEEE},
    doi = {10.1109/TPAMI.2013.17},
    url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6409353}
    }

  • Yao Hu, Debing Zhang, Jieping Ye, Xuelong Li, and Xiaofei He. Fast and accurate matrix completion via truncated nuclear norm regularization. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(9):2117-2130, 2013. doi:10.1109/TPAMI.2012.271
    [BibTeX] [Download PDF]
    @ARTICLE{hu2013fast,
    author = {Hu, Yao and Zhang, Debing and Ye, Jieping and Li, Xuelong and He, Xiaofei},
    title = {Fast and accurate matrix completion via truncated nuclear norm regularization},
    journal = {{IEEE} {T}ransactions on {P}attern {A}nalysis and {M}achine {I}ntelligence},
    year = {2013},
    volume = {35},
    pages = {2117--2130},
    number = {9},
    publisher = {IEEE},
    doi = {10.1109/TPAMI.2012.271},
    url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6389682}
    }

  • Yalin Wang, Lei Yuan, Jie Shi, Alexander Greve, Jieping Ye, Arthur W. Toga, Allan L. Reiss, and Paul M. Thompson. Applying tensor-based morphometry to parametric surfaces can improve MRI-based disease diagnosis. NeuroImage, 74:209-230, 2013. doi:10.1016/j.neuroimage.2013.02.011
    [BibTeX] [Download PDF]
    @ARTICLE{wang2013applying,
    author = {Wang, Yalin and Yuan, Lei and Shi, Jie and Greve, Alexander and Ye, Jieping and Toga, Arthur W and Reiss, Allan L and Thompson, Paul M},
    title = {Applying tensor-based morphometry to parametric surfaces can improve {MRI}-based disease diagnosis},
    journal = {{N}euro{I}mage},
    year = {2013},
    volume = {74},
    pages = {209--230},
    publisher = {Elsevier},
    doi = {10.1016/j.neuroimage.2013.02.011},
    url = {http://www.sciencedirect.com/science/article/pii/S1053811913001389}
    }

  • Shuai Huang, Jing Li, Jieping Ye, Adam Fleisher, Kewei Chen, Teresa Wu, Eric Reiman, Alzheimer’s Disease Neuroimaging Initiative, and others. A sparse structure learning algorithm for Gaussian Bayesian network identification from high-dimensional data. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(6):1328-1342, 2013.
    [BibTeX] [Download PDF]
    @ARTICLE{huang2013sparse,
    author = {Huang, Shuai and Li, Jing and Ye, Jieping and Fleisher, Adam and Chen, Kewei and Wu, Teresa and Reiman, Eric and Alzheimer's Disease Neuroimaging Initiative and others},
    title = {A sparse structure learning algorithm for {G}aussian {B}ayesian network identification from high-dimensional data},
    journal = {{IEEE} {T}ransactions on {P}attern {A}nalysis and {M}achine {I}ntelligence},
    year = {2013},
    volume = {35},
    pages = {1328--1342},
    number = {6},
    publisher = {IEEE},
    url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6212515}
    }

  • Jianhui Chen, Lei Tang, Jun Liu, and Jieping Ye. A convex formulation for learning a shared predictive structure from multiple tasks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(5):1025-1038, 2013. doi:http://doi.ieeecomputersociety.org/10.1109/TPAMI.2012.129
    [BibTeX] [Download PDF]
    @ARTICLE{chen2013convex,
    author = {Chen, Jianhui and Tang, Lei and Liu, Jun and Ye, Jieping},
    title = {A convex formulation for learning a shared predictive structure from multiple tasks},
    journal = {{IEEE} {T}ransactions on {P}attern {A}nalysis and {M}achine {I}ntelligence},
    year = {2013},
    volume = {35},
    pages = {1025--1038},
    number = {5},
    publisher = {IEEE},
    doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2012.129},
    url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6296661}
    }

  • Ji Liu, Przemyslaw Musialski, Peter Wonka, and Jieping Ye. Tensor completion for estimating missing values in visual data. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(1):208-220, 2013. doi:http://doi.ieeecomputersociety.org/10.1109/TPAMI.2012.39
    [BibTeX] [Download PDF]
    @ARTICLE{liu2013tensor,
    author = {Liu, Ji and Musialski, Przemyslaw and Wonka, Peter and Ye, Jieping},
    title = {Tensor completion for estimating missing values in visual data},
    journal = {{IEEE} {T}ransactions on {P}attern {A}nalysis and {M}achine {I}ntelligence},
    year = {2013},
    volume = {35},
    pages = {208--220},
    number = {1},
    publisher = {IEEE},
    doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2012.39},
    url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6138863}
    }

  • Rita Chattopadhyay, Zheng Wang, Wei Fan, Ian Davidson, Sethuraman Panchanathan, and Jieping Ye. Batch mode active sampling based on marginal probability distribution matching. ACM Transactions on Knowledge Discovery from Data, 7(3):13, 2013. doi:10.1145/2513092.2513094
    [BibTeX] [Download PDF]
    @ARTICLE{chattopadhyay2013batch,
    author = {Chattopadhyay, Rita and Wang, Zheng and Fan, Wei and Davidson, Ian and Panchanathan, Sethuraman and Ye, Jieping},
    title = {Batch mode active sampling based on marginal probability distribution matching},
    journal = {{ACM} {T}ransactions on {K}nowledge {D}iscovery from {D}ata},
    year = {2013},
    volume = {7},
    pages = {13},
    number = {3},
    publisher = {ACM},
    doi = {10.1145/2513092.2513094},
    url = {http://dl.acm.org/citation.cfm?id=2513094}
    }

  • Zheng Zhao, Lei Wang, Huan Liu, and Jieping Ye. On similarity preserving feature selection. IEEE Transactions on Knowledge and Data Engineering, 25(3):619-632, 2013. doi:10.1109/TKDE.2011.222
    [BibTeX] [Download PDF]
    @ARTICLE{zhao2013similarity,
    author = {Zhao, Zheng and Wang, Lei and Liu, Huan and Ye, Jieping},
    title = {On similarity preserving feature selection},
    journal = {{IEEE} {T}ransactions on {K}nowledge and {D}ata {E}ngineering},
    year = {2013},
    volume = {25},
    pages = {619--632},
    number = {3},
    publisher = {IEEE},
    doi = {10.1109/TKDE.2011.222},
    url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6051436}
    }

2012

  • Pinghua Gong, Jieping Ye, and Chang-shui Zhang. Multi-stage multi-task feature learning. In Advances in Neural Information Processing Systems, pages 1988-1996, 2012.
    [BibTeX] [Download PDF]
    @inproceedings{gong2012multi,
    title={Multi-stage multi-task feature learning},
    author={Gong, Pinghua and Ye, Jieping and Zhang, Chang-shui},
    booktitle={{A}dvances in {N}eural {I}nformation {P}rocessing {S}ystems},
    pages={1988--1996},
    year={2012},
    url={http://www.yelabs.net/publications/2012_NIPS_MultiStage.pdf}
    }

  • Chao Zhang, Lei Zhang, and Jieping Ye. Generalization bounds for domain adaptation. In Advances in Neural Information Processing Systems, pages 3320-3328, 2012.
    [BibTeX] [Download PDF]
    @inproceedings{zhang2012generalization,
    title={Generalization bounds for domain adaptation},
    author={Zhang, Chao and Zhang, Lei and Ye, Jieping},
    booktitle={{A}dvances in {N}eural {I}nformation {P}rocessing {S}ystems},
    pages={3320--3328},
    year={2012},
    url={http://www.yelabs.net/publications/2012_NIPS_BoundDA.pdf}
    }

  • Binbin Lin, Sen Yang, Chiyuan Zhang, Jieping Ye, and Xiaofei He. Multi-task vector field learning. In Advances in Neural Information Processing Systems, pages 287-295, 2012.
    [BibTeX] [Download PDF]
    @inproceedings{lin2012multi,
    title={Multi-task vector field learning},
    author={Lin, Binbin and Yang, Sen and Zhang, Chiyuan and Ye, Jieping and He, Xiaofei},
    booktitle={{A}dvances in {N}eural {I}nformation {P}rocessing {S}ystems},
    pages={287--295},
    year={2012},
    url={http://www.yelabs.net/publications/2012_NIPS_MultiTaskVFL.pdf}
    }

  • Lei Yuan, Yalin Wang, Paul M. Thompson, Vaibhav A. Narayan, and Jieping Ye. Multi-source learning for joint analysis of incomplete multi-modality neuroimaging data. In Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 1149-1157, 2012.
    [BibTeX] [Download PDF]
    @inproceedings{yuan2012multi,
    title={Multi-source learning for joint analysis of incomplete multi-modality neuroimaging data},
    author={Yuan, Lei and Wang, Yalin and Thompson, Paul M and Narayan, Vaibhav A and Ye, Jieping},
    booktitle={{P}roceedings of the 18th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={1149--1157},
    year={2012},
    url={http://www.yelabs.net/publications/2012_KDD_MultiSource.pdf}
    }

  • Rita Chattopadhyay, Zheng Wang, Wei Fan, Ian Davidson, Sethuraman Panchanathan, and Jieping Ye. Batch mode active sampling based on marginal probability distribution matching. In Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 741-749, 2012.
    [BibTeX] [Download PDF]
    @inproceedings{chattopadhyay2012batch,
    title={Batch mode active sampling based on marginal probability distribution matching},
    author={Chattopadhyay, Rita and Wang, Zheng and Fan, Wei and Davidson, Ian and Panchanathan, Sethuraman and Ye, Jieping},
    booktitle={{P}roceedings of the 18th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={741-749},
    year={2012},
    url={http://www.yelabs.net/publications/2012_KDD_BatchModeAL.pdf}
    }

  • Jiayu Zhou, Jun Liu, Vaibhav A. Narayan, and Jieping Ye. Modeling disease progression via fused sparse group Lasso. In Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 1095-1103, 2012.
    [BibTeX] [Download PDF]
    @inproceedings{zhou2012modeling,
    title={Modeling disease progression via fused sparse group {L}asso},
    author={Zhou, Jiayu and Liu, Jun and Narayan, Vaibhav A and Ye, Jieping},
    booktitle={{P}roceedings of the 18th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={1095--1103},
    year={2012},
    url={http://www.yelabs.net/publications/2012_KDD_DiseaseProg.pdf}
    }

  • Sen Yang, Lei Yuan, Ying-Cheng Lai, Xiaotong Shen, Peter Wonka, and Jieping Ye. Feature grouping and selection over an undirected graph. In Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 922-930, 2012.
    [BibTeX] [Download PDF]
    @inproceedings{yang2012feature,
    title={Feature grouping and selection over an undirected graph},
    author={Yang, Sen and Yuan, Lei and Lai, Ying-Cheng and Shen, Xiaotong and Wonka, Peter and Ye, Jieping},
    booktitle={{P}roceedings of the 18th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={922--930},
    year={2012},
    url={http://www.yelabs.net/publications/2012_KDD_UndirectedGraph.pdf}
    }

  • Shuo Xiang, Yunzhang Zhu, Xiaotong Shen, and Jieping Ye. Optimal exact least squares rank minimization. In Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 480-488, 2012.
    [BibTeX] [Download PDF]
    @inproceedings{xiang2012optimal,
    title={Optimal exact least squares rank minimization},
    author={Xiang, Shuo and Zhu, Yunzhang and Shen, Xiaotong and Ye, Jieping},
    booktitle={{P}roceedings of the 18th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={480--488},
    year={2012},
    url={http://www.yelabs.net/publications/2012_KDD_LSRankMin.pdf}
    }

  • Pinghua Gong, Jieping Ye, and Changshui Zhang. Robust multi-task feature learning. In Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 895-903, 2012.
    [BibTeX] [Download PDF]
    @inproceedings{gong2012robust,
    title={Robust multi-task feature learning},
    author={Gong, Pinghua and Ye, Jieping and Zhang, Changshui},
    booktitle={{P}roceedings of the 18th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={895--903},
    year={2012},
    url={http://www.yelabs.net/publications/2012_KDD_RobustMTL.pdf}
    }

  • Yao Hu, Debing Zhang, Jun Liu, Jieping Ye, and Xiaofei He. Accelerated singular value thresholding for matrix completion. In Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 298-306, 2012.
    [BibTeX] [Download PDF]
    @inproceedings{hu2012accelerated,
    title={Accelerated singular value thresholding for matrix completion},
    author={Hu, Yao and Zhang, Debing and Liu, Jun and Ye, Jieping and He, Xiaofei},
    booktitle={{P}roceedings of the 18th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={298--306},
    year={2012},
    url={http://www.yelabs.net/publications/2012_KDD_AccSVT.pdf}
    }

  • Jieping Ye and Jun Liu. Sparse methods for biomedical data. ACM SIGKDD Explorations Newsletter, 14(1):4-15, 2012. doi:10.1145/2408736.2408739
    [BibTeX] [Download PDF]
    @article{ye2012sparse,
    title={Sparse methods for biomedical data},
    author={Ye, Jieping and Liu, Jun},
    journal={{ACM} {SIGKDD} {E}xplorations {N}ewsletter},
    volume={14},
    number={1},
    pages={4--15},
    year={2012},
    publisher={ACM},
    doi = {10.1145/2408736.2408739},
    url={http://www.ncbi.nlm.nih.gov/pubmed/24076585}
    }

  • Sudhir Kumar, Maxwell Sanderford, Vanessa E. Gray, Jieping Ye, and Li Liu. Evolutionary diagnosis method for variants in personal exomes. Nature Methods, 9(9):855-856, 2012. doi:10.1038/nmeth.2147
    [BibTeX] [Download PDF]
    @article{kumar2012evolutionary,
    title={Evolutionary diagnosis method for variants in personal exomes},
    author={Kumar, Sudhir and Sanderford, Maxwell and Gray, Vanessa E and Ye, Jieping and Liu, Li},
    journal={{N}ature {M}ethods},
    volume={9},
    number={9},
    pages={855--856},
    year={2012},
    publisher={Nature Publishing Group},
    doi={10.1038/nmeth.2147},
    url={http://www.nature.com/nmeth/journal/v9/n9/full/nmeth.2147.html}
    }

  • Lei Yuan, Yalin Wang, Paul M. Thompson, Vaibhav A. Narayan, and Jieping Ye. Multi-source feature learning for joint analysis of incomplete multiple heterogeneous neuroimaging data. Neuroimage, 61(3):622-632, 2012. doi:10.1016/j.neuroimage.2012.03.059
    [BibTeX] [Download PDF]
    @article{yuan2012multi,
    title={Multi-source feature learning for joint analysis of incomplete multiple heterogeneous neuroimaging data},
    author={Yuan, Lei and Wang, Yalin and Thompson, Paul M and Narayan, Vaibhav A and Ye, Jieping},
    journal={{N}euroImage},
    volume={61},
    number={3},
    pages={622--632},
    year={2012},
    publisher={Elsevier},
    doi={10.1016/j.neuroimage.2012.03.059},
    url={http://www.ncbi.nlm.nih.gov/pubmed/22498655}
    }

  • Jieping Ye, Michael Farnum, Eric Yang, Rudi Verbeeck, Victor Lobanov, Nandini Raghavan, Gerald Novak, Allitia DiBernardo, Vaibhav A. Narayan, and others. Sparse learning and stability selection for predicting MCI to AD conversion using baseline ADNI data. BMC Neurology, 12(1):46, 2012. doi:10.1093/bioinformatics/bts518
    [BibTeX] [Download PDF]
    @article{ye2012sparse,
    title={Sparse learning and stability selection for predicting {MCI} to {AD} conversion using baseline {ADNI} data},
    author={Ye, Jieping and Farnum, Michael and Yang, Eric and Verbeeck, Rudi and Lobanov, Victor and Raghavan, Nandini and Novak, Gerald and DiBernardo, Allitia and Narayan, Vaibhav A and others},
    journal={{BMC} {N}eurology},
    volume={12},
    number={1},
    pages={46},
    year={2012},
    publisher={BioMed Central Ltd},
    doi = {10.1093/bioinformatics/bts518},
    url={http://www.biomedcentral.com/1471-2377/12/46}
    }

  • Sudhir Kumar, Kelly Boccia, Michael McCutchan, and Jieping Ye. Exploring spatial patterns of gene expression from Fruit Fly embryogenesis on the iPhone. Bioinformatics, 28(21):2847-2848, 2012.
    [BibTeX] [Download PDF]
    @article{kumar2012exploring,
    title={Exploring spatial patterns of gene expression from {F}ruit {F}ly embryogenesis on the i{P}hone},
    author={Kumar, Sudhir and Boccia, Kelly and McCutchan, Michael and Ye, Jieping},
    journal={{B}ioinformatics},
    volume={28},
    number={21},
    pages={2847--2848},
    year={2012},
    publisher={Oxford Univ Press},
    url={http://www.ncbi.nlm.nih.gov/pubmed/22923306}
    }

  • Lei Yuan, Alexander Woodard, Shuiwang Ji, Yuan Jiang, Zhi-Hua Zhou, Sudhir Kumar, and Jieping Ye. Learning sparse representations for fruit-fly gene expression pattern image annotation and retrieval. BMC Bioinformatics, 13(1):107, 2012. doi:10.1186/1471-2105-13-107
    [BibTeX] [Download PDF]
    @article{yuan2012learning,
    title={Learning sparse representations for fruit-fly gene expression pattern image annotation and retrieval},
    author={Yuan, Lei and Woodard, Alexander and Ji, Shuiwang and Jiang, Yuan and Zhou, Zhi-Hua and Kumar, Sudhir and Ye, Jieping},
    journal={{BMC} {B}ioinformatics},
    volume={13},
    number={1},
    pages={107},
    year={2012},
    publisher={BioMed Central Ltd},
    doi={10.1186/1471-2105-13-107},
    url={http://www.biomedcentral.com/1471-2105/13/107/}
    }

  • Ji Liu, Peter Wonka, and Jieping Ye. A multi-stage framework for Dantzig selector and Lasso. Journal of Machine Learning Research, 13(1):1189-1219, 2012.
    [BibTeX] [Download PDF]
    @article{liu2012multi,
    title={A multi-stage framework for {D}antzig selector and {L}asso},
    author={Liu, Ji and Wonka, Peter and Ye, Jieping},
    journal={{J}ournal of {M}achine {L}earning {R}esearch},
    volume={13},
    number={1},
    pages={1189--1219},
    year={2012},
    publisher={JMLR. org},
    url={http://www.jmlr.org/papers/v13/liu12a.html}
    }

  • Rita Chattopadhyay, Qian Sun, Wei Fan, Ian Davidson, Sethuraman Panchanathan, and Jieping Ye. Multisource domain adaptation and its application to early detection of fatigue. ACM Transactions on Knowledge Discovery from Data, 6(4):18, 2012. doi:10.1145/2382577.2382582
    [BibTeX] [Download PDF]
    @article{chattopadhyay2012multisource,
    title={Multisource domain adaptation and its application to early detection of fatigue},
    author={Chattopadhyay, Rita and Sun, Qian and Fan, Wei and Davidson, Ian and Panchanathan, Sethuraman and Ye, Jieping},
    journal={{ACM} {T}ransactions on {K}nowledge {D}iscovery from {D}ata},
    volume={6},
    number={4},
    pages={18},
    year={2012},
    publisher={ACM},
    doi = {10.1145/2382577.2382582},
    url={http://dl.acm.org/citation.cfm?id=2382582}
    }

  • Jianhui Chen, Ji Liu, and Jieping Ye. Learning incoherent sparse and low-rank patterns from multiple tasks. ACM Transactions on Knowledge Discovery from Data, 5(4):22, 2012. doi:10.1145/2086737.2086742
    [BibTeX] [Download PDF]
    @article{chen2012learning,
    title={Learning incoherent sparse and low-rank patterns from multiple tasks},
    author={Chen, Jianhui and Liu, Ji and Ye, Jieping},
    journal={{ACM} {T}ransactions on {K}nowledge {D}iscovery from {D}ata},
    volume={5},
    number={4},
    pages={22},
    year={2012},
    publisher={ACM},
    doi = {10.1145/2086737.2086742},
    url={http://dl.acm.org/citation.cfm?id=2086742}
    }

  • Rita Chattopadhyay, Mark Jesunathadas, Brach Poston, Marco Santello, Jieping Ye, and Sethuraman Panchanathan. A subject-independent method for automatically grading electromyographic features during a fatiguing contraction. IEEE Transactions on Biomedical Engineering, 59(6):1749-1757, 2012. doi:10.1109/TBME.2012.2193881
    [BibTeX] [Download PDF]
    @article{chattopadhyay2012subject,
    title={A Subject-Independent Method for Automatically Grading Electromyographic Features During a Fatiguing Contraction},
    author={Chattopadhyay, Rita and Jesunathadas, Mark and Poston, Brach and Santello, Marco and Ye, Jieping and Panchanathan, Sethuraman},
    journal={{IEEE} {T}ransactions on {B}iomedical {E}ngineering},
    volume={59},
    number={6},
    pages={1749--1757},
    year={2012},
    publisher={IEEE},
    doi={10.1109/TBME.2012.2193881},
    url={http://www.ncbi.nlm.nih.gov/pubmed/22498666}
    }

  • Ying-Xin Li, Shuiwang Ji, Sudhir Kumar, Jieping Ye, and Zhi-Hua Zhou. Drosophila gene expression pattern annotation through multi-instance multi-label learning. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 9(1):98-112, 2012. doi:10.1109/TCBB.2011.73
    [BibTeX] [Download PDF]
    @article{li2012drosophila,
    title={Drosophila gene expression pattern annotation through multi-instance multi-label learning},
    author={Li, Ying-Xin and Ji, Shuiwang and Kumar, Sudhir and Ye, Jieping and Zhou, Zhi-Hua},
    journal={{IEEE}/{ACM} {T}ransactions on {C}omputational {B}iology and {B}ioinformatics},
    volume={9},
    number={1},
    pages={98--112},
    year={2012},
    publisher={IEEE},
    doi={10.1109/TCBB.2011.73},
    url={http://www.ncbi.nlm.nih.gov/pubmed/20824158}
    }

2011

  • Jun Liu, Liang Sun, and Jieping Ye. Projection onto a nonnegative max-heap. In Advances in Neural Information Processing Systems, pages 487-495, 2011.
    [BibTeX] [Download PDF]
    @inproceedings{liu2011projection,
    title={Projection onto A Nonnegative Max-Heap},
    author={Liu, Jun and Sun, Liang and Ye, Jieping},
    booktitle={{A}dvances in {N}eural {I}nformation {P}rocessing {S}ystems},
    pages={487--495},
    year={2011},
    url={http://www.yelab.net/publications/2011_NIPS_Projection.pdf}
    }

  • Lei Yuan, Jun Liu, and Jieping Ye. Efficient methods for overlapping group Lasso. In Advances in Neural Information Processing Systems, pages 352-360, 2011.
    [BibTeX] [Download PDF]
    @inproceedings{yuan2011efficient,
    title={Efficient Methods for Overlapping Group {L}asso},
    author={Yuan, Lei and Liu, Jun and Ye, Jieping},
    booktitle={{A}dvances in {N}eural {I}nformation {P}rocessing {S}ystems},
    pages={352--360},
    year={2011},
    url={http://www.yelab.net/publications/2011_NIPS_Efficient.pdf}
    }

  • Jiayu Zhou, Jianhui Chen, and Jieping Ye. Clustered multi-task learning via alternating structure optimization. In Advances in Neural Information Processing Systems, pages 702-710, 2011.
    [BibTeX] [Download PDF]
    @inproceedings{zhou2011clustered,
    title={Clustered Multi-Task Learning Via Alternating Structure Optimization},
    author={Zhou, Jiayu and Chen, Jianhui and Ye, Jieping},
    booktitle={{A}dvances in {N}eural {I}nformation {P}rocessing {S}ystems},
    pages={702--710},
    year={2011},
    url={http://www.yelab.net/publications/2011_NIPS_Clustered.pdf}
    }

  • Qian Sun, Chattopadhyay Rita, Sethuraman Panchanathan, and Jieping Ye. A two-stage weighting framework for multi-source domain adaptation. In Advances in Neural Information Processing Systems, pages 505-513, 2011.
    [BibTeX] [Download PDF]
    @inproceedings{sun2011two,
    title={A Two-Stage Weighting Framework for Multi-Source Domain Adaptation},
    author={Sun, Qian and Rita, Chattopadhyay and Panchanathan, Sethuraman and Ye, Jieping},
    booktitle={{A}dvances in {N}eural {I}nformation {P}rocessing {S}ystems},
    pages={505--513},
    year={2011},
    url={http://www.yelab.net/publications/2011_NIPS_TwoStage.pdf}
    }

  • Shuai Huang, Jing Li, Jieping Ye, Kewei Chen, Teresa Wu, Adam Fleisher, and Eric Reiman. Identifying Alzheimer’s disease-related brain regions from multi-modality neuroimaging data using sparse composite linear discrimination analysis. In Advances in Neural Information Processing Systems, pages 1431-1439, 2011.
    [BibTeX] [Download PDF]
    @inproceedings{huang2011identifying,
    title={Identifying {A}lzheimer’s Disease-Related Brain Regions from Multi-Modality Neuroimaging Data using Sparse Composite Linear Discrimination Analysis},
    author={Huang, Shuai and Li, Jing and Ye, Jieping and Chen, Kewei and Wu, Teresa and Fleisher, Adam and Reiman, Eric},
    booktitle={{A}dvances in {N}eural {I}nformation {P}rocessing {S}ystems},
    pages={1431--1439},
    year={2011},
    url={http://www.yelab.net/publications/2011_NIPS_Identifying.pdf}
    }

  • Jianhui Chen, Jiayu Zhou, and Jieping Ye. Integrating low-rank and group-sparse structures for robust multi-task learning. In Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 42-50, 2011.
    [BibTeX] [Download PDF]
    @inproceedings{chen2011integrating,
    title={Integrating Low-Rank and Group-Sparse Structures for Robust Multi-Task Learning},
    author={Chen, Jianhui and Zhou, Jiayu and Ye, Jieping},
    booktitle={{P}roceedings of the 17th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={42--50},
    year={2011},
    url={http://www.yelab.net/publications/2011_KDD_Integrating.pdf}
    }

  • Shuai Huang, Jing Li, Jieping Ye, Adam Fleisher, Kewei Chen, Teresa Wu, and Eric Reiman. Brain effective connectivity modeling for Alzheimer’s disease study by sparse Bayesian network. In Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 931-939, 2011.
    [BibTeX] [Download PDF]
    @inproceedings{huang2011brain,
    title={Brain Effective Connectivity Modeling for {A}lzheimer’s Disease Study by Sparse {B}ayesian Network},
    author={Huang, Shuai and Li, Jing and Ye, Jieping and Fleisher, Adam and Chen, Kewei and Wu, Teresa and Reiman, Eric},
    booktitle={{P}roceedings of the 17th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={931--939},
    year={2011},
    url={http://www.yelab.net/publications/2011_KDD_Brain.pdf}
    }

  • Rita Chattopadhyay, Jieping Ye, Sethuraman Panchanathan, Ian Davidson, and Wei Fan. Multi-source domain adaptation and its application to early detection of fatigue. In Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 717-725, 2011.
    [BibTeX] [Download PDF]
    @inproceedings{chattopadhyay2011multisource,
    title={Multi-Source Domain Adaptation and Its Application to Early Detection of Fatigue},
    author={Chattopadhyay, Rita and Ye, Jieping and Panchanathan, Sethuraman and Davidson, Ian and Fan, Wei},
    booktitle={{P}roceedings of the 17th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={717--725},
    year={2011},
    url={http://www.yelab.net/publications/2011_KDD_MultiSource.pdf}
    }

  • Jiayu Zhou, Lei Yuan, Jun Liu, and Jieping Ye. A multi-task learning formulation for predicting disease progression. In Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 814-822, 2011.
    [BibTeX] [Download PDF]
    @inproceedings{zhou2011multitask,
    title={A Multi-Task Learning Formulation for Predicting Disease Progression},
    author={Zhou, Jiayu and Yuan, Lei and Liu, Jun and Ye, Jieping},
    booktitle={{P}roceedings of the 17th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={814--822},
    year={2011},
    url={http://www.yelab.net/publications/2011_KDD_MultiTask.pdf}
    }

  • Wen-Xu Wang, Ying-Cheng Lai, Celso Grebogi, and Jieping Ye. Network reconstruction based on evolutionary-game data via compressive sensing. Physical Review X, 1:21021, Dec 2011. doi:10.1103/PhysRevX.1.021021
    [BibTeX] [Download PDF]
    @article{PhysRevX.1.021021,
    title = {Network Reconstruction Based on Evolutionary-Game Data via Compressive Sensing},
    author = {Wang, Wen-Xu and Lai, Ying-Cheng and Grebogi, Celso and Ye, Jieping},
    journal={{P}hysical {R}eview {X}},
    volume = {1},
    issue = {2},
    pages = {021021},
    numpages = {7},
    year = {2011},
    month = {Dec},
    publisher = {American Physical Society},
    doi = {10.1103/PhysRevX.1.021021},
    url = {http://link.aps.org/doi/10.1103/PhysRevX.1.021021}
    }

  • Sudhir Kumar, Charlotte Konikoff, Bernard Van Emden, Christopher Busick, Kailah T. Davis, Shuiwang Ji, Lin-Wei Wu, Hector Ramos, Thomas Brody, Sethuraman Panchanathan, Jieping Ye, Timothy L. Karr, Kristyn Gerold, Michael McCutchan, and Stuart J. Newfeld. Flyexpress: visual mining of spatiotemporal patterns for genes and publications in Drosophila embryogenesis. Bioinformatics, 27(23):3319-3320, 2011. doi:10.1093/bioinformatics/btr567} url={http://www.ncbi.nlm.nih.gov/pubmed/21994220
    [BibTeX]
    @article{kumar2011flyexpress,
    title={FlyExpress: Visual Mining of Spatiotemporal Patterns for Genes and Publications in {D}rosophila Embryogenesis},
    author={Kumar, Sudhir and Konikoff, Charlotte and Van Emden, Bernard and Busick, Christopher and Davis, Kailah T. and Ji, Shuiwang and Wu, Lin-Wei and Ramos, Hector and Brody, Thomas and Panchanathan, Sethuraman and Ye, Jieping and Karr, Timothy L. and Gerold, Kristyn and McCutchan, Michael and Newfeld, Stuart J.},
    journal={{B}ioinformatics},
    volume={27},
    number={23},
    pages={3319--3320},
    year={2011},
    publisher={Oxford Univ Press},
    doi={10.1093/bioinformatics/btr567}
    url={http://www.ncbi.nlm.nih.gov/pubmed/21994220}
    }

  • Xichuan Zhou, Jieping Ye, and Yujie Feng. Tuberculosis surveillance by analyzing google trends. IEEE Transactions on Biomedical Engineering, 58(8):2247-2254, 2011. doi:10.1109/TBME.2011.2132132
    [BibTeX] [Download PDF]
    @article{zhou2011tuberculosis,
    title={Tuberculosis Surveillance by Analyzing Google Trends},
    author={Zhou, Xichuan and Ye, Jieping and Feng, Yujie},
    journal={{IEEE} {T}ransactions on {B}iomedical {E}ngineering},
    volume={58},
    number={8},
    pages={2247--2254},
    year={2011},
    publisher={IEEE},
    doi = {10.1109/TBME.2011.2132132},
    url={http://www.ncbi.nlm.nih.gov/pubmed/21435969}
    }

  • Jieping Ye, Teresa Wu, Jing Li, and Kewei Chen. Machine learning approaches for the neuroimaging study of Alzheimer’s disease. IEEE Computer, 44(4):99-101, 2011. doi:10.1109/MC.2011.117
    [BibTeX] [Download PDF]
    @article{ye2011machine,
    title = {Machine Learning Approaches for the Neuroimaging Study of {A}lzheimer's Disease},
    author = {Ye, Jieping and Wu, Teresa and Li, Jing and Chen, Kewei},
    journal = {{IEEE} {C}omputer},
    year = {2011},
    number = {4},
    pages = {99--101},
    volume = {44},
    publisher = {IEEE Computer Society Press},
    doi = {10.1109/MC.2011.117},
    url = {http://dx.doi.org/10.1109/MC.2011.117}
    }

  • Shipeng Yu, Jinbo Bi, and Jieping Ye. Matrix-variate and higher-order probabilistic projections. Data Mining and Knowledge Discovery, 22(3):372-392, 2011. doi:10.1007/s10618-010-0183-9
    [BibTeX] [Download PDF]
    @article{yu2011matrix,
    title={Matrix-variate and higher-order probabilistic projections},
    author={Yu, Shipeng and Bi, Jinbo and Ye, Jieping},
    year={2011},
    journal={{D}ata {M}ining and {K}nowledge {D}iscovery},
    volume={22},
    number={3},
    publisher={Springer US},
    pages={372-392},
    doi = {10.1007/s10618-010-0183-9},
    url = {http://link.springer.com/article/10.1007%2Fs10618-010-0183-9}
    }

  • Liang Sun, Shuiwang Ji, and Jieping Ye. Canonical correlation analysis for multi-label classification: a least squares formulation, extensions and analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1(33):194-200, 2011. doi:10.1109/TPAMI.2010.160
    [BibTeX] [Download PDF]
    @article{sun2011cca,
    title = {Canonical Correlation Analysis for Multi-Label Classification: A Least Squares Formulation, Extensions and Analysis},
    author = {Sun, Liang and Ji, Shuiwang and Ye, Jieping},
    journal = {{IEEE} {T}ransactions on {P}attern {A}nalysis and {M}achine {I}ntelligence},
    year = {2011},
    number = {33},
    pages = {194--200},
    volume = {1},
    publisher = {IEEE},
    doi = {10.1109/TPAMI.2010.160},
    url = {http://www.ncbi.nlm.nih.gov/pubmed/20733223}
    }

2010

  • Ji Liu, Peter Wonka, and Jieping Ye. Multi-stage Dantzig selector. In Advances in Neural Information Processing Systems, pages 1450-1458, 2010.
    [BibTeX] [Download PDF]
    @inproceedings{liu2010multi,
    title={Multi-stage {D}antzig selector},
    author={Liu, Ji and Wonka, Peter and Ye, Jieping},
    booktitle={{A}dvances in {N}eural {I}nformation {P}rocessing {S}ystems},
    pages={1450--1458},
    year={2010},
    url={http://www.yelab.net/publications/2010_NIPS_MultiStageDantzig.pdf}
    }

  • Jun Liu and Jieping Ye. Moreau-Yosida regularization for grouped tree structure learning. In Advances in Neural Information Processing Systems, pages 1459-1467, 2010.
    [BibTeX] [Download PDF]
    @inproceedings{liu2010moreau,
    title={Moreau-{Y}osida regularization for grouped tree structure learning},
    author={Liu, Jun and Ye, Jieping},
    booktitle={{A}dvances in {N}eural {I}nformation {P}rocessing {S}ystems},
    pages={1459--1467},
    year={2010},
    url={http://www.yelab.net/publications/2010_NIPS_TreeLasso.pdf}
    }

  • Jun Liu, Lei Yuan, and Jieping Ye. An efficient algorithm for a class of fused Lasso problems. In Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 323-332, 2010.
    [BibTeX] [Download PDF]
    @inproceedings{liu2010efficient,
    title={An efficient algorithm for a class of fused {L}asso problems},
    author={Liu, Jun and Yuan, Lei and Ye, Jieping},
    booktitle={{P}roceedings of the 16th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={323--332},
    year={2010},
    url={http://www.yelab.net/publications/2010_KDD_FusedLasso.pdf}
    }

  • Liang Sun, Betul Ceran, and Jieping Ye. A scalable two-stage approach for a class of dimensionality reduction techniques. In Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 313-322, 2010.
    [BibTeX] [Download PDF]
    @inproceedings{sun2010scalable,
    title={A scalable two-stage approach for a class of dimensionality reduction techniques},
    author={Sun, Liang and Ceran, Betul and Ye, Jieping},
    booktitle={{P}roceedings of the 16th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={313--322},
    year={2010},
    url={http://www.yelab.net/publications/2010_KDD_DRT.pdf}
    }

  • Ting Kei Pong, Paul Tseng, Shuiwang Ji, and Jieping Ye. Trace norm regularization: reformulations, algorithms, and multi-task learning. SIAM Journal on Optimization, 20(6):3465-3489, 2010.
    [BibTeX] [Download PDF]
    @article{pong2010trace,
    title={Trace norm regularization: reformulations, algorithms, and multi-task learning},
    author={Pong, Ting Kei and Tseng, Paul and Ji, Shuiwang and Ye, Jieping},
    journal={{SIAM} {J}ournal on {O}ptimization},
    volume={20},
    number={6},
    pages={3465--3489},
    year={2010},
    publisher={SIAM},
    url={http://www.optimization-online.org/DB_FILE/2009/06/2325.pdf}
    }

  • Shuiwang Ji, Lei Tang, Shipeng Yu, and Jieping Ye. A shared-subspace learning framework for multi-label classification. ACM Transactions on Knowledge Discovery from Data, 4(2):8, 2010.
    [BibTeX] [Download PDF]
    @article{ji2010shared,
    title={A shared-subspace learning framework for multi-label classification},
    author={Ji, Shuiwang and Tang, Lei and Yu, Shipeng and Ye, Jieping},
    journal={{ACM} {T}ransactions on {K}nowledge {D}iscovery from {D}ata},
    volume={4},
    number={2},
    pages={8},
    year={2010},
    publisher={ACM},
    url={http://www.yelab.net/publications/2010_TKDD_Ji.pdf}
    }

  • Ivaylo Ilinkin, Jieping Ye, and Ravi Janardan. Multiple structure alignment and consensus identification for proteins. BMC Bioinformatics, 11(1):71, 2010.
    [BibTeX] [Download PDF]
    @article{ilinkin2010multiple,
    title={Multiple structure alignment and consensus identification for proteins},
    author={Ilinkin, Ivaylo and Ye, Jieping and Janardan, Ravi},
    journal={{BMC} {B}ioinformatics},
    volume={11},
    number={1},
    pages={71},
    year={2010},
    publisher={BioMed Central Ltd},
    url={http://www.biomedcentral.com/1471-2105/11/71}
    }

  • Shuai Huang, Jing Li, Liang Sun, Jieping Ye, Adam Fleisher, Teresa Wu, Kewei Chen, and Eric Reiman. Learning brain connectivity of Alzheimer’s disease by sparse inverse covariance estimation. Neuroimage, 50(3):935-949, 2010.
    [BibTeX] [Download PDF]
    @article{HuangLSYFWCRI10,
    author = {Shuai Huang and
    Jing Li and
    Liang Sun and
    Jieping Ye and
    Adam Fleisher and
    Teresa Wu and
    Kewei Chen and
    Eric Reiman},
    title = {Learning brain connectivity of {A}lzheimer's disease by sparse inverse
    covariance estimation},
    journal = {{N}euroImage},
    volume = {50},
    number = {3},
    pages = {935--949},
    year = {2010},
    url = {http://www.sciencedirect.com/science/article/pii/S1053811909014281}
    }

2009

  • Jun Liu, Shuiwang Ji, and Jieping Ye. SLEP: sparse learning with efficient projections. Arizona State University, 2009.
    [BibTeX] [Download PDF]
    @article{liu2009slep,
    title={{SLEP}: Sparse learning with efficient projections},
    author={Liu, Jun and Ji, Shuiwang and Ye, Jieping},
    journal={Arizona {S}tate {U}niversity},
    year={2009},
    url={http://www.yelab.net/publications/2009_slep.pdf}
    }

  • Liang Sun, Jun Liu, Jianhui Chen, and Jieping Ye. Efficient recovery of jointly sparse vectors. In Advances in Neural Information Processing Systems, pages 1812-1820, 2009.
    [BibTeX] [Download PDF]
    @inproceedings{sun2009efficient,
    title={Efficient recovery of jointly sparse vectors},
    author={Sun, Liang and Liu, Jun and Chen, Jianhui and Ye, Jieping},
    booktitle={{Advances} in {N}eural {I}nformation {P}rocessing {S}ystems},
    pages={1812--1820},
    year={2009},
    url={http://www.yelab.net/publications/2009_nips_efficientrecovery.pdf}
    }

  • Shuai Huang, Jing Li, Liang Sun, Jun Liu, Teresa Wu, Kewei Chen, Adam Fleisher, Eric Reiman, and Jieping Ye. Learning brain connectivity of Alzheimer’s disease from neuroimaging data. In Advances in Neural Information Processing Systems, pages 808-816, 2009.
    [BibTeX] [Download PDF]
    @inproceedings{huang2009learning,
    title={Learning brain connectivity of {A}lzheimer's disease from neuroimaging data},
    author={Huang, Shuai and Li, Jing and Sun, Liang and Liu, Jun and Wu, Teresa and Chen, Kewei and Fleisher, Adam and Reiman, Eric and Ye, Jieping},
    booktitle={{Advances} in {N}eural {I}nformation {P}rocessing {S}ystems},
    pages={808--816},
    year={2009},
    url={http://www.yelab.net/publications/2009_nips_learningbrainconnectivity.pdf}
    }

  • Ji Liu, Przemyslaw Musialski, Peter Wonka, and Jieping Ye. Tensor completion for estimating missing values in visual data.. In Proceedings of the 12th International Conference on Computer Vision, pages 2114-2121, 2009.
    [BibTeX] [Download PDF]
    @inproceedings{LiuMWY09,
    title = {Tensor completion for estimating missing values in visual data.},
    author = {Liu, Ji and Musialski, Przemyslaw and Wonka, Peter and Ye, Jieping},
    booktitle = {{P}roceedings of the 12th {I}nternational {C}onference on {C}omputer {V}ision},
    pages = {2114-2121},
    year = {2009},
    url = {http://www.yelab.net/publications/2009_iccv_tensorcompletion.pdf}
    }

  • Jun Liu, Shuiwang Ji, and Jieping Ye. Multi-task feature learning via efficient l 2, 1-norm minimization. In Proceedings of the twenty-fifth conference on Uncertainty in Artificial Intelligence, pages 339-348, 2009.
    [BibTeX] [Download PDF]
    @inproceedings{liu2009multi,
    title={Multi-task feature learning via efficient l 2, 1-norm minimization},
    author={Liu, Jun and Ji, Shuiwang and Ye, Jieping},
    booktitle={{P}roceedings of the Twenty-Fifth Conference on {U}ncertainty in {A}rtificial {I}ntelligence},
    pages={339--348},
    year={2009},
    url={http://www.yelab.net/publications/2009_uai_multitaskfeaturelearning.pdf}
    }

  • Liang Sun, Rinkal Patel, Jun Liu, Kewei Chen, Teresa Wu, Jing Li, Eric Reiman, and Jieping Ye. Mining brain region connectivity for Alzheimer’s disease study via sparse inverse covariance estimation. In Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 1335-1344, 2009.
    [BibTeX] [Download PDF]
    @inproceedings{sun2009mining,
    title={Mining brain region connectivity for {A}lzheimer's disease study via sparse inverse covariance estimation},
    author={Sun, Liang and Patel, Rinkal and Liu, Jun and Chen, Kewei and Wu, Teresa and Li, Jing and Reiman, Eric and Ye, Jieping},
    booktitle={{P}roceedings of the 15th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={1335--1344},
    year={2009},
    url={http://www.yelab.net/publications/2009_kdd_miningbrainregionconnectivity.pdf}
    }

  • Bao-Hong Shen, Shuiwang Ji, and Jieping Ye. Mining discrete patterns via binary matrix factorization. In Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 757-766, 2009.
    [BibTeX] [Download PDF]
    @inproceedings{shen2009mining,
    title={Mining discrete patterns via binary matrix factorization},
    author={Shen, Bao-Hong and Ji, Shuiwang and Ye, Jieping},
    booktitle={{P}roceedings of the 15th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={757--766},
    year={2009},
    url={http://www.yelab.net/publications/2009_kdd_miningdiscretepatterns.pdf}
    }

  • Jun Liu, Jianhui Chen, and Jieping Ye. Large-scale sparse logistic regression. In Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 547-556, 2009.
    [BibTeX] [Download PDF]
    @inproceedings{liu2009large,
    title={Large-scale sparse logistic regression},
    author={Liu, Jun and Chen, Jianhui and Ye, Jieping},
    booktitle={{P}roceedings of the 15th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={547--556},
    year={2009},
    url={http://www.yelab.net/publications/2009_kdd_large-scalesparse.pdf}
    }

  • Shuiwang Ji, Lei Yuan, Ying-Xin Li, Zhi-Hua Zhou, Sudhir Kumar, and Jieping Ye. Drosophila gene expression pattern annotation using sparse features and term-term interactions. In Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 407-416, 2009.
    [BibTeX] [Download PDF]
    @inproceedings{ji2009drosophila,
    title={Drosophila gene expression pattern annotation using sparse features and term-term interactions},
    author={Ji, Shuiwang and Yuan, Lei and Li, Ying-Xin and Zhou, Zhi-Hua and Kumar, Sudhir and Ye, Jieping},
    booktitle={{P}roceedings of the 15th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={407--416},
    year={2009},
    url={http://www.yelab.net/publications/2009_kdd_drosophilageneexpression.pdf}
    }

  • Jianhui Chen, Lei Tang, Jun Liu, and Jieping Ye. A convex formulation for learning shared structures from multiple tasks. In Proceedings of the 26th Annual International Conference on Machine Learning, pages 137-144, 2009.
    [BibTeX] [Download PDF]
    @inproceedings{chen2009convex,
    title={A convex formulation for learning shared structures from multiple tasks},
    author={Chen, Jianhui and Tang, Lei and Liu, Jun and Ye, Jieping},
    booktitle={{P}roceedings of the 26th {A}nnual {I}nternational {C}onference on {M}achine {L}earning},
    pages={137--144},
    year={2009},
    url={http://www.yelab.net/publications/2009_icml_Aconvexformulation.pdf}
    }

  • Liang Sun, Shuiwang Ji, and Jieping Ye. A least squares formulation for a class of generalized eigenvalue problems in machine learning. In Proceedings of the 26th Annual International Conference on Machine Learning, pages 977-984, 2009.
    [BibTeX] [Download PDF]
    @inproceedings{sun2009least,
    title={A least squares formulation for a class of generalized eigenvalue problems in machine learning},
    author={Sun, Liang and Ji, Shuiwang and Ye, Jieping},
    booktitle={{P}roceedings of the 26th {A}nnual {I}nternational {C}onference on {M}achine {L}earning},
    pages={977--984},
    year={2009},
    url={http://www.yelab.net/publications/2009_icml_Aleastsquaresformulation.pdf}
    }

  • Shuiwang Ji and Jieping Ye. An accelerated gradient method for trace norm minimization. In Proceedings of the 26th Annual International Conference on Machine Learning, pages 457-464, 2009.
    [BibTeX] [Download PDF]
    @inproceedings{ji2009accelerated,
    title={An accelerated gradient method for trace norm minimization},
    author={Ji, Shuiwang and Ye, Jieping},
    booktitle={{P}roceedings of the 26th {A}nnual {I}nternational {C}onference on {M}achine {L}earning},
    pages={457--464},
    year={2009},
    url={http://www.yelab.net/publications/2009_icml_Anacceleratedgradientmethod.pdf}
    }

  • Jun Liu and Jieping Ye. Efficient Euclidean projections in linear time. In Proceedings of the 26th Annual International Conference on Machine Learning, pages 657-664, 2009.
    [BibTeX] [Download PDF]
    @inproceedings{liu2009efficient,
    title={Efficient {E}uclidean projections in linear time},
    author={Liu, Jun and Ye, Jieping},
    booktitle={{P}roceedings of the 26th {A}nnual {I}nternational {C}onference on {M}achine {L}earning},
    pages={657--664},
    year={2009},
    url={http://www.yelab.net/publications/2009_icml_efficienteuclideanprojections.pdf}
    }

  • Zenglin Xu, Rong Jin, Jieping Ye, Michael R. Lyu, and Irwin King. Non-monotonic feature selection. In Proceedings of the 26th Annual International Conference on Machine Learning, pages 1145-1152, 2009.
    [BibTeX] [Download PDF]
    @inproceedings{xu2009non,
    title={Non-monotonic feature selection},
    author={Xu, Zenglin and Jin, Rong and Ye, Jieping and Lyu, Michael R and King, Irwin},
    booktitle={{P}roceedings of the 26th {A}nnual {I}nternational {C}onference on {M}achine {L}earning},
    pages={1145--1152},
    year={2009},
    url={http://www.yelab.net/publications/2009_icml_non-monotonicfeatureselection.pdf}
    }

  • Liu Yang, Rong Jin, and Jieping Ye. Online learning by Ellipsoid method. In Proceedings of the 26th Annual International Conference on Machine Learning, pages 1153-1160, 2009.
    [BibTeX] [Download PDF]
    @inproceedings{yang2009online,
    title={Online learning by {E}llipsoid method},
    author={Yang, Liu and Jin, Rong and Ye, Jieping},
    booktitle={{P}roceedings of the 26th {A}nnual {I}nternational {C}onference on {M}achine {L}earning},
    pages={1153--1160},
    year={2009},
    url={http://www.yelab.net/publications/2009_icml_onlinelearning.pdf}
    }

  • Ying-Xin Li, Shuiwang Ji, Sudhir Kumar, Jieping Ye, and Zhi-Hua Zhou. Drosophila gene expression pattern annotation through multi-instance multi-label learning. , pages 1445-1450, 2009.
    [BibTeX] [Download PDF]
    @inproceedings{IJCAI09432,
    title = {Drosophila Gene Expression Pattern Annotation through Multi-Instance Multi-Label Learning},
    author = {Li, Ying-Xin and Ji, Shuiwang and Kumar, Sudhir and Ye, Jieping and Zhou, Zhi-Hua},
    conference = {{P}roceedings of the 21th {I}nternational {J}oint {C}onference on {A}rtificial {I}ntelligence},
    pages={1445--1450},
    year = {2009},
    url = {http://www.yelab.net/publications/2009_ijcai_drosophilageneexpression.pdf}
    }

  • Jun Liu, Jianhui Chen, Songcan Chen, and Jieping Ye. Learning the optimal neighborhood kernel for classification.. In Proceedings of the 21th International Joint Conference on Artificial Intelligence, pages 1144-1149, 2009.
    [BibTeX] [Download PDF]
    @inproceedings{liu2009learning,
    title={Learning the Optimal Neighborhood Kernel for Classification.},
    author={Liu, Jun and Chen, Jianhui and Chen, Songcan and Ye, Jieping},
    booktitle={{P}roceedings of the 21th {I}nternational {J}oint {C}onference on {A}rtificial {I}ntelligence},
    pages={1144--1149},
    year={2009},
    url={http://www.yelab.net/publications/2009_ijcai_learningoptimalneighborhoodkernel.pdf}
    }

  • Liang Sun, Shuiwang Ji, Shipeng Yu, and Jieping Ye. On the equivalence between canonical correlation analysis and orthonormalized partial least squares.. In Proceedings of the 21th International Joint Conference on Artificial Intelligence, volume 9, pages 1230-1235, 2009.
    [BibTeX] [Download PDF]
    @inproceedings{sun2009equivalence,
    title={On the Equivalence between Canonical Correlation Analysis and Orthonormalized Partial Least Squares.},
    author={Sun, Liang and Ji, Shuiwang and Yu, Shipeng and Ye, Jieping},
    booktitle={{P}roceedings of the 21th {I}nternational {J}oint {C}onference on {A}rtificial {I}ntelligence},
    volume={9},
    pages={1230--1235},
    year={2009},
    url={http://www.yelab.net/publications/2009_ijcai_equivalencebetweenccaandopls.pdf}
    }

  • Zheng Zhao, Liang Sun, Shipeng Yu, Huan Liu, and Jieping Ye. Multiclass probabilistic kernel discriminant analysis.. In Proceedings of the 21th International Joint Conference on Artificial Intelligence, pages 1363-1368, 2009.
    [BibTeX] [Download PDF]
    @inproceedings{zhao2009multiclass,
    title={Multiclass Probabilistic Kernel Discriminant Analysis.},
    author={Zhao, Zheng and Sun, Liang and Yu, Shipeng and Liu, Huan and Ye, Jieping},
    booktitle={{P}roceedings of the 21th {I}nternational {J}oint {C}onference on {A}rtificial {I}ntelligence},
    pages={1363--1368},
    year={2009},
    url={http://www.yelab.net/publications/2009_ijcai_multiclassprobabilistic.pdf}
    }

  • Lei Tang, Jianhui Chen, and Jieping Ye. On multiple kernel learning with multiple labels.. In Proceedings of the 21th International Joint Conference on Artificial Intelligence, pages 1255-1260, 2009.
    [BibTeX] [Download PDF]
    @inproceedings{tang2009multiple,
    title={On Multiple Kernel Learning with Multiple Labels.},
    author={Tang, Lei and Chen, Jianhui and Ye, Jieping},
    booktitle={{P}roceedings of the 21th {I}nternational {J}oint {C}onference on {A}rtificial {I}ntelligence},
    pages={1255--1260},
    year={2009},
    url={http://www.yelab.net/publications/2009_ijcai_multiplekernellearning.pdf}
    }

  • Shuiwang Ji and Jieping Ye. Linear dimensionality reduction for multi-label classification.. In Proceedings of the 21th International Joint Conference on Artificial Intelligence, volume 9, pages 1077-1082, 2009.
    [BibTeX] [Download PDF]
    @inproceedings{ji2009linear,
    title={Linear Dimensionality Reduction for Multi-label Classification.},
    author={Ji, Shuiwang and Ye, Jieping},
    booktitle={{P}roceedings of the 21th {I}nternational {J}oint {C}onference on {A}rtificial {I}ntelligence},
    volume={9},
    pages={1077--1082},
    year={2009},
    url={http://www.yelab.net/publications/2009_ijcai_lineardimensionalityreduction.pdf}
    }

  • Shuiwang Ji, Ying-Xin Li, Zhi-Hua Zhou, Sudhir Kumar, and Jieping Ye. A bag-of-words approach for Drosophila gene expression pattern annotation. BMC bioinformatics, 10(1):119, 2009.
    [BibTeX] [Download PDF]
    @article{ji2009bag,
    title={A bag-of-words approach for {D}rosophila gene expression pattern annotation},
    author={Ji, Shuiwang and Li, Ying-Xin and Zhou, Zhi-Hua and Kumar, Sudhir and Ye, Jieping},
    journal={{BMC} bioinformatics},
    volume={10},
    number={1},
    pages={119},
    year={2009},
    publisher={BioMed Central Ltd},
    url={http://www.biomedcentral.com/1471-2105/10/119/}
    }

  • Mingrui Wu and Jieping Ye. A small sphere and large margin approach for novelty detection using training data with outliers. IEEE Transactions on Pattern Analysis and Machine Intelligence, 31(11):2088-2092, 2009. doi:10.1109/TPAMI.2009.24
    [BibTeX] [Download PDF]
    @article{wu2009small,
    title={A small sphere and large margin approach for novelty detection using training data with outliers},
    author={Wu, Mingrui and Ye, Jieping},
    journal={{IEEE} {T}ransactions on {P}attern {A}nalysis and {M}achine {I}ntelligence},
    volume={31},
    number={11},
    pages={2088--2092},
    year={2009},
    publisher={IEEE},
    doi={10.1109/TPAMI.2009.24},
    ISSN={0162-8828},
    url={http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=4760149&url=http%3A%2F%2Fieeexplore.ieee.org%2Fiel5%2F34%2F5256019%2F04760149.pdf%3Farnumber%3D4760149}
    }

  • Saif Ali, Jieping Ye, Anshuman Razdan, and Peter Wonka. Compressed facade displacement maps. IEEE Transactions on Visualization and Computer Graphics, 15(2):262-273, 2009. doi:10.1109/TVCG.2008.98
    [BibTeX] [Download PDF]
    @article{ali2009compressed,
    title={Compressed facade displacement maps},
    author={Ali, Saif and Ye, Jieping and Razdan, Anshuman and Wonka, Peter},
    journal={{IEEE} {T}ransactions on {V}isualization and {C}omputer {G}raphics},
    volume={15},
    number={2},
    pages={262--273},
    year={2009},
    publisher={IEEE},
    doi={10.1109/TVCG.2008.98},
    ISSN={1077-2626},
    url={http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=4585376&url=http%3A%2F%2Fieeexplore.ieee.org%2Fiel5%2F2945%2F4756206%2F04585376.pdf%3Farnumber%3D4585376}
    }

2008

  • Shuiwang Ji, Liang Sun, Rong Jin, and Jieping Ye. Multi-label multiple kernel learning. In Advances in Neural Information Processing Systems, pages 777-784. , 2009.
    [BibTeX] [Download PDF]
    @incollection{NIPS2008_3574,
    title = {Multi-label Multiple Kernel Learning},
    author = {Shuiwang Ji and Liang Sun and Jin, Rong and Ye, Jieping},
    booktitle = {{A}dvances in {N}eural {I}nformation {P}rocessing {S}ystems},
    pages = {777--784},
    year = {2009},
    url = {http://www.yelab.net/publications/2008_nips_multilabelmultikernel.pdf}
    }

  • Jieping Ye, Kewei Chen, Teresa Wu, Jing Li, Zheng Zhao, Rinkal Patel, Min Bae, Ravi Janardan, Huan Liu, Gene Alexander, and Eric Reiman. Heterogeneous data fusion for Alzheimer’s disease study. In Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 1025-1033, 2008.
    [BibTeX] [Download PDF]
    @inproceedings{Ye:2008:HDF:1401890.1402012,
    author = {Ye, Jieping and Chen, Kewei and Wu, Teresa and Li, Jing and Zhao, Zheng and Patel, Rinkal and Bae, Min and Janardan, Ravi and Liu, Huan and Alexander, Gene and Reiman, Eric},
    title = {Heterogeneous Data Fusion for {A}lzheimer's Disease Study},
    booktitle = {{P}roceedings of the 14th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    year = {2008},
    pages = {1025--1033},
    url = {http://www.yelab.net/publications/2008_kdd_heterogeneousdatafusion.pdf}
    }

  • Zheng Zhao, Jiangxin Wang, Huan Liu, Jieping Ye, and Yung Chang. Identifying biologically relevant genes via multiple heterogeneous data sources. In Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 839-847, 2008.
    [BibTeX] [Download PDF]
    @inproceedings{Zhao:2008:IBR:1401890.1401990,
    author = {Zhao, Zheng and Wang, Jiangxin and Liu, Huan and Ye, Jieping and Chang, Yung},
    title = {Identifying Biologically Relevant Genes via Multiple Heterogeneous Data Sources},
    booktitle = {{P}roceedings of the 14th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    year = {2008},
    pages = {839--847},
    url = {http://www.yelab.net/publications/2008_kdd_identifyingbiologicallyrelevantgenes.pdf}
    }

  • Shuiwang Ji, Lei Tang, Shipeng Yu, and Jieping Ye. Extracting shared subspace for multi-label classification. In Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 381-389, 2008.
    [BibTeX] [Download PDF]
    @inproceedings{Ji:2008:ESS:1401890.1401939,
    author = {Ji, Shuiwang and Tang, Lei and Yu, Shipeng and Ye, Jieping},
    title = {Extracting Shared Subspace for Multi-label Classification},
    booktitle = {{P}roceedings of the 14th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    year = {2008},
    pages = {381--389},
    url = {http://www.yelab.net/publications/2008_kdd_extractingsharedsubspace.pdf}
    }

  • Liang Sun, Shuiwang Ji, and Jieping Ye. Hypergraph spectral learning for multi-label classification. In Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 668-676, 2008.
    [BibTeX] [Download PDF]
    @inproceedings{Sun:2008:HSL:1401890.1401971,
    author = {Sun, Liang and Ji, Shuiwang and Ye, Jieping},
    title = {Hypergraph Spectral Learning for Multi-label Classification},
    booktitle = {{P}roceedings of the 14th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    year = {2008},
    pages = {668--676},
    url = {http://www.yelab.net/publications/2008_kdd_hypergraphspectrallearning.pdf}
    }

  • Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Mingrui Wu, and Jieping Ye. Learning subspace kernels for classification. In Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 106-114, 2008.
    [BibTeX] [Download PDF]
    @inproceedings{Chen:2008:LSK:1401890.1401908,
    author = {Chen, Jianhui and Ji, Shuiwang and Ceran, Betul and Li, Qi and Wu, Mingrui and Ye, Jieping},
    title = {Learning Subspace Kernels for Classification},
    booktitle = {{P}roceedings of the 14th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    year = {2008},
    pages = {106--114},
    url = {http://www.yelab.net/publications/2008_kdd_learningsubspacekernel.pdf}
    }

  • Liang Sun, Shuiwang Ji, and Jieping Ye. A least squares formulation for canonical correlation analysis. In Proceedings of the 25th International Conference on Machine Learning, pages 1024-1031, 2008.
    [BibTeX] [Download PDF]
    @inproceedings{Sun:2008:LSF:1390156.1390285,
    author = {Sun, Liang and Ji, Shuiwang and Ye, Jieping},
    title = {A Least Squares Formulation for Canonical Correlation Analysis},
    booktitle = {{P}roceedings of the 25th {I}nternational {C}onference on {M}achine {L}earning},
    year = {2008},
    pages = {1024--1031},
    url = {http://www.yelab.net/publications/2008_icml_aleastsquareformulation.pdf}
    }

  • Jianhui Chen and Jieping Ye. Training svm with indefinite kernels. In Proceedings of the 25th International Conference on Machine Learning, pages 136-143, 2008.
    [BibTeX] [Download PDF]
    @inproceedings{Chen:2008:TSI:1390156.1390174,
    author = {Chen, Jianhui and Ye, Jieping},
    title = {Training SVM with Indefinite Kernels},
    booktitle = {{P}roceedings of the 25th {I}nternational {C}onference on {M}achine {L}earning},
    year = {2008},
    pages = {136--143},
    url = {http://www.yelab.net/publications/2008_icml_trainingsvmwithindefinitekernels.pdf}
    }

  • Shuiwang Ji and Jieping Ye. A unified framework for generalized linear discriminant analysis. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pages 1-7, 2008.
    [BibTeX] [Download PDF]
    @INPROCEEDINGS{Ji08aunified,
    author = {Shuiwang Ji and Jieping Ye},
    title = {A Unified Framework for Generalized Linear Discriminant Analysis},
    booktitle = {{IEEE} {C}omputer {S}ociety {C}onference on {C}omputer {V}ision and {P}attern {R}ecognition},
    year = {2008},
    url={http://www.yelab.net/publications/2008_cvpr_aunifiedframework.pdf},
    pages = {1--7}
    }

  • Shuiwang Ji, Liang Sun, Rong Jin, Sudhir Kumar, and Jieping Ye. Automated annotation of Drosophila gene expression patterns using a controlled vocabulary. Bioinformatics, 24(17):1881-1888, 2008.
    [BibTeX] [Download PDF]
    @article{ji2008automated,
    title={Automated annotation of {D}rosophila gene expression patterns using a controlled vocabulary},
    author={Ji, Shuiwang and Sun, Liang and Jin, Rong and Kumar, Sudhir and Ye, Jieping},
    journal={{B}ioinformatics},
    volume={24},
    number={17},
    pages={1881--1888},
    year={2008},
    url={http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2519157/},
    publisher={Oxford Univ Press}
    }

  • Liang Sun, Shuiwang Ji, and Jieping Ye. Adaptive diffusion kernel learning from biological networks for protein function prediction. BMC Bioinformatics, 9(1):162, 2008.
    [BibTeX] [Download PDF]
    @article{sun2008adaptive,
    title={Adaptive diffusion kernel learning from biological networks for protein function prediction},
    author={Sun, Liang and Ji, Shuiwang and Ye, Jieping},
    journal={{BMC} {B}ioinformatics},
    volume={9},
    number={1},
    pages={162},
    year={2008},
    url={http://www.biomedcentral.com/1471-2105/9/162},
    publisher={BioMed Central Ltd}
    }

  • Shuiwang Ji and Jieping Ye. Generalized linear discriminant analysis: a unified framework and efficient model selection. IEEE Transactions on Neural Networks, 19(10):1768-1782, 2008.
    [BibTeX] [Download PDF]
    @article{ji2008generalized,
    title={Generalized linear discriminant analysis: a unified framework and efficient model selection},
    author={Ji, Shuiwang and Ye, Jieping},
    journal={{IEEE} {T}ransactions on {N}eural {N}etworks},
    volume={19},
    number={10},
    pages={1768--1782},
    year={2008},
    url={http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=4633689&queryText%3DGeneralized+linear+discriminant+analysis%3A+a+unified+framework+and+efficient+model+selection},
    publisher={IEEE}
    }

  • Jieping Ye, Shuiwang Ji, and Jianhui Chen. Multi-class discriminant kernel learning via convex programming. Journal of Machine Learning Research, 9:719-758, 2008.
    [BibTeX] [Download PDF]
    @article{ye2008multi,
    title={Multi-class discriminant kernel learning via convex programming},
    author={Ye, Jieping and Ji, Shuiwang and Chen, Jianhui},
    journal={{J}ournal of {M}achine {L}earning {R}esearch},
    volume={9},
    pages={719--758},
    year={2008},
    url={http://www.jmlr.org/papers/v9/ye08b.html},
    publisher={JMLR. org}
    }

  • Shuiwang Ji and Jieping Ye. Kernel uncorrelated and regularized discriminant analysis: a theoretical and computational study. IEEE Transactions on Knowledge and Data Engineering, 20(10):1311-1321, 2008.
    [BibTeX] [Download PDF]
    @article{ji2008kernel,
    title={Kernel uncorrelated and regularized discriminant analysis: a theoretical and computational study},
    author={Ji, Shuiwang and Ye, Jieping},
    journal={{IEEE} {T}ransactions on {K}nowledge and {D}ata {E}ngineering},
    volume={20},
    number={10},
    pages={1311--1321},
    year={2008},
    url={http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=4479466&queryText%3DKernel+uncorrelated+and+regularized+discriminant+analysis%3A+a+theoretical+and+computational+study},
    publisher={IEEE}
    }

  • Jieping Ye, Jianhui Chen, Ravi Janardan, and Sudhir Kumar. Developmental stage annotation of Drosophila gene expression pattern images via an entire solution path for lda. ACM Transactions on Knowledge Discovery from Data, 2(1):4, 2008.
    [BibTeX] [Download PDF]
    @article{ye2008developmental,
    title={Developmental stage annotation of {D}rosophila gene expression pattern images via an entire solution path for LDA},
    author={Ye, Jieping and Chen, Jianhui and Janardan, Ravi and Kumar, Sudhir},
    journal={{ACM} {T}ransactions on {K}nowledge {D}iscovery from {D}ata},
    volume={2},
    number={1},
    pages={4},
    year={2008},
    url={http://dl.acm.org/citation.cfm?id=1342320.1342324&coll=DL&dl=ACM&CFID=618882433&CFTOKEN=70808534},
    publisher={ACM}
    }

2007

  • Jieping Ye, Zheng Zhao, and Mingrui Wu. Discriminative k-means for clustering. In Advances in Neural Information Processing Systems, pages 1649-1656, 2008.
    [BibTeX] [Download PDF]
    @inproceedings{ye2008discriminative,
    title={Discriminative k-means for clustering},
    author={Ye, Jieping and Zhao, Zheng and Wu, Mingrui},
    booktitle={{A}dvances in {N}eural {I}nformation {P}rocessing {S}ystems},
    pages={1649--1656},
    year={2008},
    url = {http://www.yelab.net/publications/2007_nips_discriminativekmeans.pdf}
    }

  • Jieping Ye, Shuiwang Ji, and Jianhui Chen. Learning the kernel matrix in discriminant analysis via quadratically constrained quadratic programming. In Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 854-863, 2007.
    [BibTeX] [Download PDF]
    @inproceedings{ye2007learning,
    title={Learning the kernel matrix in discriminant analysis via quadratically constrained quadratic programming},
    author={Ye, Jieping and Ji, Shuiwang and Chen, Jianhui},
    booktitle={{P}roceedings of the 13th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={854--863},
    year={2007},
    url = {http://www.yelab.net/publications/2007_kdd_learningkernelmatrix.pdf}
    }

  • Jianhui Chen, Zheng Zhao, Jieping Ye, and Huan Liu. Nonlinear adaptive distance metric learning for clustering. In Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 123-132, 2007.
    [BibTeX] [Download PDF]
    @inproceedings{chen2007nonlinear,
    title={Nonlinear adaptive distance metric learning for clustering},
    author={Chen, Jianhui and Zhao, Zheng and Ye, Jieping and Liu, Huan},
    booktitle={{P}roceedings of the 13th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={123--132},
    year={2007},
    url = {http://www.yelab.net/publications/2007_kdd_nonlinearadaptive.pdf}
    }

  • Jieping Ye. Least squares linear discriminant analysis. In Proceedings of the 24th International Conference on Machine Learning, pages 1087-1093, 2007.
    [BibTeX] [Download PDF]
    @inproceedings{ye2007least,
    title={Least squares linear discriminant analysis},
    author={Ye, Jieping},
    booktitle={{P}roceedings of the 24th {I}nternational {C}onference on {M}achine {L}earning},
    pages={1087--1093},
    year={2007},
    url = {http://www.yelab.net/publications/2007_icml_leastsquareslinear.pdf}
    }

  • Jieping Ye, Jianhui Chen, and Shuiwang Ji. Discriminant kernel and regularization parameter learning via semidefinite programming. In Proceedings of the 24th International Conference on Machine Learning, pages 1095-1102, 2007.
    [BibTeX] [Download PDF]
    @inproceedings{ye2007discriminant,
    title={Discriminant kernel and regularization parameter learning via semidefinite programming},
    author={Ye, Jieping and Chen, Jianhui and Ji, Shuiwang},
    booktitle={{P}roceedings of the 24th {I}nternational {C}onference on {M}achine {L}earning},
    pages={1095--1102},
    year={2007},
    url = {http://www.yelab.net/publications/2007_icml_discriminantkernel.pdf}
    }

  • Jianhui Chen, Jieping Ye, and Qi Li. Integrating global and local structures: a least squares framework for dimensionality reduction. In IEEE Conference on Computer Vision and Pattern Recognition, pages 1-8, 2007.
    [BibTeX] [Download PDF]
    @inproceedings{chen2007integrating,
    title={Integrating global and local structures: a least squares framework for dimensionality reduction},
    author={Chen, Jianhui and Ye, Jieping and Li, Qi},
    booktitle={{IEEE} {C}onference on {C}omputer {V}ision and {P}attern {R}ecognition},
    pages={1--8},
    year={2007},
    url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=4270065&queryText%3DIntegrating+global+and+local+structures%3A+a+least+squares+framework+for+dimensionality+reduction}
    }

  • Vineeth Nallure Balasubramanian, Jieping Ye, and Sethuraman Panchanathan. Biased manifold embedding: a framework for person-independent head pose estimation. In IEEE Conference on Computer Vision and Pattern Recognition, pages 1-7. IEEE, 2007.
    [BibTeX] [Download PDF]
    @inproceedings{balasubramanian2007biased,
    title={Biased manifold embedding: A framework for person-independent head pose estimation},
    author={Balasubramanian, Vineeth Nallure and Ye, Jieping and Panchanathan, Sethuraman},
    booktitle={{IEEE} {C}onference on {C}omputer {V}ision and {P}attern {R}ecognition},
    pages={1--7},
    year={2007},
    publisher={IEEE},
    url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4270305}
    }

  • Jieping Ye, Zheng Zhao, and Huan Liu. Adaptive distance metric learning for clustering. In IEEE Conference on Computer Vision and Pattern Recognition, pages 1-7. IEEE, 2007.
    [BibTeX] [Download PDF]
    @inproceedings{ye2007adaptive,
    title={Adaptive distance metric learning for clustering},
    author={Ye, Jieping and Zhao, Zheng and Liu, Huan},
    booktitle={{IEEE} {C}onference on {C}omputer {V}ision and {P}attern {R}ecognition},
    pages={1--7},
    year={2007},
    publisher={IEEE},
    url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4270128}
    }

  • Jieping Ye and Tao Xiong. Svm versus least squares svm. In International Conference on Artificial Intelligence and Statistics, pages 644-651, 2007.
    [BibTeX] [Download PDF]
    @inproceedings{ye2007svm,
    title={SVM versus least squares SVM},
    author={Ye, Jieping and Xiong, Tao},
    booktitle={{I}nternational {C}onference on {A}rtificial {I}ntelligence and {S}tatistics},
    pages={644--651},
    year={2007},
    url = {http://www.yelab.net/publications/2007_aistats_svmvslssvm.pdf}
    }

2006

  • Jieping Ye, Tao Xiong, Qi Li, Ravi Janardan, Jinbo Bi, Vladimir Cherkassky, and Chandra Kambhamettu. Efficient model selection for regularized linear discriminant analysis. In Proceedings of the 15th ACM International Conference on Information and Knowledge Management, pages 532-539, 2006.
    [BibTeX] [Download PDF]
    @INPROCEEDINGS{ye2006efficient,
    author = {Ye, Jieping and Xiong, Tao and Li, Qi and Janardan, Ravi and Bi, Jinbo and Cherkassky, Vladimir and Kambhamettu, Chandra},
    title = {Efficient model selection for regularized linear discriminant analysis},
    booktitle = {{P}roceedings of the 15th {ACM} {I}nternational {C}onference on {I}nformation and {K}nowledge {M}anagement},
    year = {2006},
    pages = {532--539},
    url = {http://www.yelab.net/publications/2006_CIKM_LDA.pdf}
    }

  • Jieping Ye, Ivaylo Ilinkin, Ravi Janardan, and Adam Isom. Multiple structure alignment and consensus identification for proteins. In Algorithms in Bioinformatics, pages 115-125. , 2006.
    [BibTeX] [Download PDF]
    @INCOLLECTION{ye2006multiple,
    author = {Ye, Jieping and Ilinkin, Ivaylo and Janardan, Ravi and Isom, Adam},
    title = {Multiple structure alignment and consensus identification for proteins},
    booktitle = {{A}lgorithms in {B}ioinformatics},
    year = {2006},
    pages = {115--125},
    url = {http://www.yelab.net/publications/2006_WABI_ProAlign.pdf}
    }

  • Jieping Ye and Tie Wang. Regularized discriminant analysis for high dimensional, low sample size data. In Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 454-463, 2006.
    [BibTeX] [Download PDF]
    @INPROCEEDINGS{ye2006regularized,
    author = {Ye, Jieping and Wang, Tie},
    title = {Regularized discriminant analysis for high dimensional, low sample size data},
    booktitle = {{P}roceedings of the 12th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    year = {2006},
    pages = {454--463},
    url = {http://www.yelab.net/publications/2006_KDD_RegDA.pdf}
    }

  • Jieping Ye, Jianhui Chen, Qi Li, and Sudhir Kumar. Classification of Drosophila embryonic developmental stage range based on gene expression pattern images.. In Proceedings of Computational Systems Bioinformatics Conference, pages 293-298, 2005.
    [BibTeX] [Download PDF]
    @INPROCEEDINGS{ye2005classification,
    author = {Ye, Jieping and Chen, Jianhui and Li, Qi and Kumar, Sudhir},
    title = {Classification of {D}rosophila embryonic developmental stage range based on gene expression pattern images.},
    booktitle = {{P}roceedings of {C}omputational {S}ystems {B}ioinformatics {C}onference},
    year = {2005},
    pages = {293--298},
    url = {http://www.yelab.net/publications/2006_CSB_DrosClassify.pdf}
    }

  • Jieping Ye and Tao Xiong. Null space versus orthogonal linear discriminant analysis. In Proceedings of the 23rd International Conference on Machine Learning, pages 1073-1080, 2006.
    [BibTeX] [Download PDF]
    @INPROCEEDINGS{ye2006null,
    author = {Ye, Jieping and Xiong, Tao},
    title = {Null space versus orthogonal linear discriminant analysis},
    booktitle = {{P}roceedings of the 23rd {I}nternational {C}onference on {M}achine {L}earning},
    year = {2006},
    pages = {1073--1080},
    url = {http://www.yelab.net/publications/2006_ICML_OrthLDA.pdf}
    }

  • Jieping Ye, Tao Xiong, and Ravi Janardan. CPM: a covariance-preserving projection method.. In Proceedings of the 6th Siam Conference on Data Mining, pages 24-34, 2006.
    [BibTeX] [Download PDF]
    @INPROCEEDINGS{ye2006cpm,
    author = {Ye, Jieping and Xiong, Tao and Janardan, Ravi},
    title = {{CPM}: A Covariance-preserving Projection Method.},
    booktitle = {{P}roceedings of the 6th {S}IAM {C}onference on {D}ata {M}ining},
    year = {2006},
    pages = {24--34},
    url = {http://www.yelab.net/publications/2006_SDM_CPM.pdf}
    }

  • Tao Xiong, Jieping Ye, and Vladimir Cherkassky. Kernel uncorrelated and orthogonal discriminant analysis: a unified approach. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition, volume 1, pages 125-131, 2006.
    [BibTeX] [Download PDF]
    @INPROCEEDINGS{xiong2006kernel,
    author = {Xiong, Tao and Ye, Jieping and Cherkassky, Vladimir},
    title = {Kernel uncorrelated and orthogonal discriminant analysis: a unified approach},
    booktitle = {{IEEE} {C}omputer {S}ociety {C}onference on {C}omputer {V}ision and {P}attern {R}ecognition},
    year = {2006},
    volume = {1},
    pages = {125--131},
    url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1640750&tag=1}
    }

  • Jieping Ye, Ravi Janardan, Qi Li, and Haesun Park. Feature reduction via generalized uncorrelated linear discriminant analysis. IEEE Transactions on Knowledge and Data Engineering, 18(10):1312-1322, 2006. doi:http://doi.ieeecomputersociety.org/10.1109/TKDE.2006.160
    [BibTeX] [Download PDF]
    @ARTICLE{ye2006feature,
    author = {Ye, Jieping and Janardan, Ravi and Li, Qi and Park, Haesun},
    title = {Feature reduction via generalized uncorrelated linear discriminant analysis},
    journal = {{IEEE} {T}ransactions on {K}nowledge and {D}ata {E}ngineering},
    year = {2006},
    volume = {18},
    pages = {1312--1322},
    number = {10},
    publisher = {IEEE},
    doi = {http://doi.ieeecomputersociety.org/10.1109/TKDE.2006.160},
    url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1683768}
    }

  • Jieping Ye and Tao Xiong. Computational and theoretical analysis of null space and orthogonal linear discriminant analysis. Journal of Machine Learning Research, 7:1183-1204, 2006.
    [BibTeX] [Download PDF]
    @ARTICLE{ye2006computational,
    author = {Ye, Jieping and Xiong, Tao},
    title = {Computational and theoretical analysis of null space and orthogonal linear discriminant analysis},
    journal = {{J}ournal of {M}achine {L}earning {R}esearch},
    year = {2006},
    volume = {7},
    pages = {1183--1204},
    publisher = {JMLR. org},
    url = {http://www.jmlr.org/papers/volume7/ye06a/ye06a.pdf}
    }

  • Qi Li, Jieping Ye, and Chandra Kambhamettu. Spatial interest pixels (SIPs): useful low-level features of visual media data. Multimedia Tools and Applications, 30(1):89-108, 2006.
    [BibTeX] [Download PDF]
    @ARTICLE{li2006spatial,
    author = {Li, Qi and Ye, Jieping and Kambhamettu, Chandra},
    title = {Spatial interest pixels ({SIP}s): useful low-level features of visual media data},
    journal = {{M}ultimedia {T}ools and {A}pplications},
    year = {2006},
    volume = {30},
    pages = {89--108},
    number = {1},
    publisher = {Springer},
    url = {http://link.springer.com/article/10.1007/s11042-006-0009-3}
    }

2005

  • Chris HQ Ding and Jieping Ye. 2-Dimensional Singular Value Decomposition for 2D maps and images.. In Proceedings of the 2005 SIAM International Conference on Data Mining, pages 32-43, 2005.
    [BibTeX] [Download PDF]
    @inproceedings{ding20052,
    title={2-{D}imensional {S}ingular {V}alue {D}ecomposition for {2D} Maps and Images.},
    author={Ding, Chris HQ and Ye, Jieping},
    booktitle = {{P}roceedings of the 2005 {SIAM} {I}nternational {C}onference on {D}ata {M}ining},
    pages={32-43},
    year={2005},
    url={http://www.yelab.net/publications/2005_SDM_2dsvd.pdf}
    }

  • Jieping Ye. Characterization of a family of algorithms for generalized discriminant analysis on undersampled problems. In Journal of Machine Learning Research, pages 483-502, 2005.
    [BibTeX] [Download PDF]
    @inproceedings{ye2005characterization,
    title={Characterization of a family of algorithms for generalized discriminant analysis on undersampled problems},
    author={Ye, Jieping},
    booktitle={{J}ournal of {M}achine {L}earning {R}esearch},
    pages={483--502},
    year={2005},
    url={http://www.jmlr.org/papers/v6/ye05a.html}
    }

  • Jieping Ye, Qi Li, Hui Xiong, Haesun Park, Ravi Janardan, and Vipin Kumar. IDR/QR: an incremental dimension reduction algorithm via qr decomposition. IEEE Transactions on Knowledge and Data Engineering, 17(9):1208-1222, 2005. doi:10.1109/TKDE.2005.148
    [BibTeX] [Download PDF]
    @article{ye2005idr,
    title={{IDR/QR}: An incremental dimension reduction algorithm via QR decomposition},
    author={Ye, Jieping and Li, Qi and Xiong, Hui and Park, Haesun and Janardan, Ravi and Kumar, Vipin},
    journal={{IEEE} {T}ransactions on {K}nowledge and {D}ata {E}ngineering},
    volume={17},
    number={9},
    pages={1208--1222},
    year={2005},
    publisher={IEEE},
    doi={10.1109/TKDE.2005.148},
    url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=1490528&sortType%3Dasc_p_Sequence%26filter%3DAND%28p_IS_Number%3A32046%29}
    }

  • Jieping Ye. Generalized low rank approximations of matrices. Machine Learning, 61(1-3):167-191, 2005. doi:10.1007/s10994-005-3561-6
    [BibTeX] [Download PDF]
    @article{ye2005generalized,
    title={Generalized low rank approximations of matrices},
    author={Ye, Jieping},
    journal={{M}achine {L}earning},
    volume={61},
    number={1-3},
    pages={167--191},
    year={2005},
    publisher={Springer},
    doi = {10.1007/s10994-005-3561-6},
    url = {http://link.springer.com/article/10.1007%2Fs10994-005-3561-6}
    }

  • Jieping Ye and Qi Li. A two-stage linear discriminant analysis via QR-decomposition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(6):929-941, 2005. doi:10.1109/TPAMI.2005.110
    [BibTeX]
    @article{ye2005two,
    title={A two-stage linear discriminant analysis via {QR}-decomposition},
    author={Ye, Jieping and Li, Qi},
    journal={{IEEE} {T}ransactions on {P}attern {A}nalysis and {M}achine {I}ntelligence},
    volume={27},
    number={6},
    pages={929--941},
    year={2005},
    publisher={IEEE},
    doi={10.1109/TPAMI.2005.110},
    ISSN={0162-8828},}

2004

  • Jieping Ye, Ravi Janardan, and Qi Li. Two-dimensional linear discriminant analysis. In Advances in Neural Information Processing Systems, pages 1569-1576, 2004.
    [BibTeX] [Download PDF]
    @inproceedings{ye2004two,
    title={Two-Dimensional Linear Discriminant Analysis},
    author={Ye, Jieping and Janardan, Ravi and Li, Qi},
    booktitle={{A}dvances in {N}eural {I}nformation {P}rocessing {S}ystems},
    pages={1569--1576},
    year={2004},
    url={http://www.yelab.net/publications/2004_NIPS_Two.pdf}
    }

  • Tao Xiong, Jieping Ye, Qi Li, and Ravi Janardan. Efficient kernel discriminant analysis via qr decomposition. In Advances in Neural Information Processing Systems, pages 1529-1536, 2004.
    [BibTeX] [Download PDF]
    @inproceedings{tao2004efficient,
    title={Efficient Kernel Discriminant Analysis via QR Decomposition},
    author={Xiong, Tao and Ye, Jieping and Li, Qi and Janardan, Ravi},
    booktitle={{A}dvances in {N}eural {I}nformation {P}rocessing {S}ystems},
    pages={1529--1536},
    year={2004},
    url={http://www.yelab.net/publications/2004_NIPS_Efficient.pdf}
    }

  • Jieping Ye, Ravi Janardan, and Qi Li. Gpca: an efficient dimension reduction scheme for image compression and retrieval. In Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 354-363, 2004.
    [BibTeX] [Download PDF]
    @inproceedings{ye2004GPCA,
    title={GPCA: An Efficient Dimension Reduction Scheme for Image Compression and Retrieval},
    author={Ye, Jieping and Janardan, Ravi and Li, Qi},
    booktitle={{P}roceedings of the 10th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={354--363},
    year={2004},
    url={http://www.yelab.net/publications/2004_KDD_GPCA.pdf}
    }

  • Jieping Ye, Qi Li, Hui Xiong, Haesum Park, Ravi Janardan, and Vipin Kumar. Idr/qr: an incremental dimension reduction algorithm via qr decomposition. In Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 364-373, 2004.
    [BibTeX] [Download PDF]
    @inproceedings{ye2004IDR,
    title={IDR/QR: An Incremental Dimension Reduction Algorithm via QR Decomposition},
    author={Ye, Jieping and Li, Qi and Xiong, Hui and Park, Haesum and Janardan, Ravi and Kumar, Vipin},
    booktitle={{P}roceedings of the 10th {ACM} {SIGKDD} {I}nternational {C}onference on {K}nowledge {D}iscovery and {D}ata {M}ining},
    pages={364--373},
    year={2004},
    url={http://www.yelab.net/publications/2004_KDD_IDR.pdf}
    }

  • Jieping Ye, Ravi Janardan, Qi Li, and Haesum Park. Feature extraction via generalized uncorrelated linear discriminant analysis. In Proceedings of the 21st International Conference on Machine Learning, pages 895-902, 2004.
    [BibTeX] [Download PDF]
    @inproceedings{ye2004feature,
    title={Feature Extraction via Generalized Uncorrelated Linear Discriminant Analysis},
    author={Ye, Jieping and Janardan, Ravi and Li, Qi and Park, Haesum},
    booktitle={{P}roceedings of the 21st {I}nternational {C}onference on {M}achine {L}earning},
    pages={895--902},
    year={2004},
    url = {http://www.yelab.net/publications/2004_ICML_Feature.pdf}
    }

  • Jieping Ye, Ravi Janardan, Qi Li, and Haesum Park. Generalized low rank approximations of matrices. In Proceedings of the 21st International Conference on Machine Learning, pages 887-894, 2004.
    [BibTeX] [Download PDF]
    @inproceedings{ye2004generalized,
    title={Generalized Low Rank Approximations of Matrices},
    author={Ye, Jieping and Janardan, Ravi and Li, Qi and Park, Haesum},
    booktitle={{P}roceedings of the 21st {I}nternational {C}onference on {M}achine {L}earning},
    pages={887--894},
    year={2004},
    url = {http://www.yelab.net/publications/2004_ICML_Generalized.pdf}
    }

  • Qi Li, Jieping Ye, and Chandra Kambhamettu. Linear projection methods in face recognition under unconstrained illumination: a comparative study. In Proceedings of the Ieee Computer Society Conference on Computer Vision and Pattern Recognition, pages 474-481, 2004.
    [BibTeX] [Download PDF]
    @inproceedings{li2004linear,
    title={Linear Projection Methods in Face Recognition under Unconstrained Illumination: A Comparative Study},
    author={Li, Qi and Ye, Jieping and Kambhamettu, Chandra},
    booktitle={{P}roceedings of the {I}EEE {C}omputer {S}ociety {C}onference on {C}omputer {V}ision and {P}attern {R}ecognition},
    volumn = {2},
    pages={474--481},
    year={2004},
    url = {http://www.yelab.net/publications/2004_CVPR_Linear.pdf}
    }

  • Jieping Ye, Tao Li, Tao Xiong, and Ravi Janardan. Using uncorrelated discriminant analysis for tissue classification with gene expression data. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 1(4):181-190, 2004. doi:10.1109/TCBB.2004.45
    [BibTeX] [Download PDF]
    @article{ye2004using,
    title={Using Uncorrelated Discriminant Analysis for Tissue Classification with Gene Expression Data},
    author={Ye, Jieping and Li, Tao and Xiong, Tao and Janardan, Ravi},
    journal={{IEEE}/{ACM} {T}ransactions on {C}omputational {B}iology and {B}ioinformatics},
    issue_date = {October 2004},
    volume = {1},
    number = {4},
    month = oct,
    year = {2004},
    issn = {1545-5963},
    pages = {181--190},
    numpages = {10},
    url = {http://dx.doi.org/10.1109/TCBB.2004.45},
    doi = {10.1109/TCBB.2004.45},
    acmid = {1042362},
    publisher = {IEEE Computer Society Press},
    address = {Los Alamitos, CA, USA},
    }

  • Jieping Ye Ye, Ravi Janardan, and Songtao Liu. Pairwise protein structure alignment based on an orientation-independent representation of the backbone geometry. Journal of Bioinformatincs and Computational Biology, 2(4):699-717, 2004. doi:10.1109/TAI.2003.1250163
    [BibTeX] [Download PDF]
    @article{ye2004pairwise,
    author = {Ye, Jieping Ye and Janardan, Ravi and Liu, Songtao},
    title = {Pairwise Protein Structure Alignment Based on an Orientation-Independent Representation of the Backbone Geometry},
    journal = {{J}ournal of {B}ioinformatincs and {C}omputational {B}iology},
    year = {2004},
    number = {4},
    pages = {699--717},
    volume = {2},
    url = {http://www.worldscientific.com/worldscinet/jbcb},
    doi={10.1109/TAI.2003.1250163},
    ISSN={1082-3409},
    }

  • Jieping Ye, Ravi Janardan, Cheonghee Park, and Haesun Park. An optimization criterion for generalized discriminant analysis on undersampled problems. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(8):982-994, 2004. doi:10.1109/TPAMI.2004.37
    [BibTeX] [Download PDF]
    @article{ye2004an,
    title = {An Optimization Criterion for Generalized Discriminant Analysis on Undersampled Problems},
    author = {Ye, Jieping and Janardan, Ravi and Park, Cheonghee and Park, Haesun},
    journal = {{IEEE} {T}ransactions on {P}attern {A}nalysis and {M}achine {I}ntelligence},
    year = {2004},
    number = {8},
    pages = {982--994},
    volume = {26},
    url = {http://www.ncbi.nlm.nih.gov/pubmed/15641729},
    doi = {10.1109/TPAMI.2004.37},
    ISSN = {0162-8828}
    }

  • Jieping Ye and Ravi Janardan. Approximate multiple protein structure alignment using the sum-of pairs distance. Journal of Computational Biology, 11(5):986-1000, 2004.
    [BibTeX] [Download PDF]
    @article{ye2004approximate,
    title = {Approximate Multiple Protein Structure Alignment Using the Sum-of pairs Distance},
    author = {Ye, Jieping and Janardan, Ravi},
    journal = {{J}ournal of {C}omputational {B}iology},
    year = {2004},
    number = {5},
    pages = {986--1000},
    volume = {11},
    url = {http://www.ncbi.nlm.nih.gov/pubmed/15700413}
    }

2003

  • Jieping Ye, Ravi Janardan, Cheong Hee Park, and Haesun Park. A new optimization criterion for generalized discriminant analysis on undersampled problems. In Proceedings of the 3rd IEEE International Conference on Data Mining, pages 419-426, 2003.
    [BibTeX] [Download PDF]
    @inproceedings{ye2003new,
    title={A new optimization criterion for generalized discriminant analysis on undersampled problems},
    author={Ye, Jieping and Janardan, Ravi and Park, Cheong Hee and Park, Haesun},
    booktitle={{P}roceedings of the 3rd {IEEE} {I}nternational {C}onference on {D}ata {M}ining},
    pages={419--426},
    year={2003},
    url={http://www.yelab.net/publications/2003_ICDM_GSVD.pdf}
    }

  • Qi Li, Jieping Ye, and Chandra Kambhamettu. Spatial interest pixels (SIPs): useful low-level features of visual media data. In Proceedings of the 3rd IEEE International Conference on Data Mining, pages 163-170, 2003.
    [BibTeX] [Download PDF]
    @inproceedings{LiYK03,
    author = {Qi Li and
    Jieping Ye and
    Chandra Kambhamettu},
    title = {Spatial Interest Pixels ({SIP}s): Useful Low-Level Features of Visual
    Media Data},
    booktitle = {{P}roceedings of the 3rd {IEEE} {I}nternational {C}onference on {D}ata {M}ining},
    pages = {163--170},
    year = {2003},
    url = {http://www.yelab.net/publications/2003_ICDM_Spatial.pdf}
    }

  • Jieping Ye, Ravi Janardan, and Songtao Liu. Pairwise protein structure alignment based on an orientation-independent representation of the backbone geometry. In 15th IEEE International Conference on Tools with Artificial Intelligence, pages 2-8, 2003.
    [BibTeX] [Download PDF]
    @inproceedings{YeJL03,
    author = {Jieping Ye and
    Ravi Janardan and
    Songtao Liu},
    title = {Pairwise Protein Structure Alignment Based on an Orientation-Independent
    Representation of the Backbone Geometry},
    booktitle = {15th {IEEE} {I}nternational {C}onference on {T}ools with {A}rtificial {I}ntelligence},
    pages = {2--8},
    year = {2003},
    url = {http://www.yelab.net/publications/2003_ICTAI_Pairwise.pdf}
    }