Ji Liu

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Xiangru LianKuaishou Technology Co., Ltd, University of RochesterVerified email at mail.xrlian.com
Ce ZhangETH ZurichVerified email at inf.ethz.ch
Yang CongState Key Laboratory of Robotics, SIA, Chinese Academy of Sciences (CAS)Verified email at sia.cn
Jieping Ye, IEEE Fellow & ACM Distin...University of Michigan & BeikeVerified email at umich.edu
Tong ZhangHKUSTVerified email at tongzhang-ml.org
Hanlin TangUniversity of RochesterVerified email at ur.rochester.edu
Stephen WrightDepartment of Computer Sciences and Wisconsin Institute for Discovery, University of WisconsinVerified email at cs.wisc.edu
Peter WonkaKing Abdullah University of Science and Technology (KAUST)Verified email at kaust.edu.sa
Haichuan YangUniversity of RochesterVerified email at rochester.edu
Junsong YuanState University of New York at BuffaloVerified email at buffalo.edu
Bo LiuAuburn UniversityVerified email at cs.umass.edu
Wei ZhangIBM T.J.Watson Research CenterVerified email at us.ibm.com
Cho-Jui HsiehUniversity of California, Los AngelesVerified email at cs.ucla.edu
Chen YuUniversity of Rochester, PhDVerified email at ur.rochester.edu
Sridhar MahadevanDirector, Data Science Lab, Adobe Research & Professor, University of Massachusetts, AmherstVerified email at cs.umass.edu
Przemyslaw MusialskiAssociate Professor, New Jersey Institute of TechnologyVerified email at njit.edu
Jiebo LuoProfessor of Computer Science, University of RochesterVerified email at cs.rochester.edu
Zhangyang (Atlas) WangUniversity of Texas at Austin & Amazon ResearchVerified email at utexas.edu
Shaoduo GanETH ZurichVerified email at inf.ethz.ch
Dan AlistarhIST AustriaVerified email at ist.ac.at

Ji Liu

University of Rochester

Verified email at cs.rochester.edu - Homepage

machine learning optimization reinforcement learning computer vision compressed sensing.


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Tensor Completion for Estimating Missing Values in Visual Data J Liu, P Musialski, P Wonka, J Ye IEEE Transactions on Pattern Analysis and Machine Intelligence 35 (1), 208-220, 2013	1268	2013
Sparse reconstruction cost for abnormal event detection Y Cong, J Yuan, J Liu CVPR 2011, 3449-3456, 2011	741	2011
Can decentralized algorithms outperform centralized algorithms? a case study for decentralized parallel stochastic gradient descent X Lian, C Zhang, H Zhang, CJ Hsieh, W Zhang, J Liu arXiv preprint arXiv:1705.09056, 2017	440	2017
An Asynchronous Parallel Stochastic Coordinate Descent Algorithm J Liu, SJ Wright, C Ré, V Bittorf, S Sridhar arXiv:1311.1873, 2013	359	2013
Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization X Lian, Y Huang, Y Li, J Liu NIPS arXiv preprint arXiv:1506.08272, 2015	354	2015
Abnormal event detection in crowded scenes using sparse representation Y Cong, J Yuan, J Liu Pattern Recognition 46 (7), 1851-1864, 2013	285	2013
Gradient sparsification for communication-efficient distributed optimization J Wangni, J Wang, J Liu, T Zhang arXiv preprint arXiv:1710.09854, 2017	253	2017
Asynchronous stochastic coordinate descent: Parallelism and convergence properties J Liu, SJ Wright SIAM Journal on Optimization 25 (1), 351-376, 2015	245	2015
Asynchronous decentralized parallel stochastic gradient descent X Lian, W Zhang, C Zhang, J Liu International Conference on Machine Learning, 3043-3052, 2018	198	2018
Staleness-aware Async-SGD for Distributed Deep Learning W Zhang, S Gupta, X Lian, J Liu IJCAI, arXiv preprint arXiv:1511.05950, 2015	189	2015
Zipml: Training linear models with end-to-end low precision, and a little bit of deep learning H Zhang, J Li, K Kara, D Alistarh, J Liu, C Zhang International Conference on Machine Learning, 4035-4043, 2017	158*	2017
Learning incoherent sparse and low-rank patterns from multiple tasks J Chen, J Liu, J Ye ACM Transaction on Knowledge Discovery from Data 5 (4), 2012	145	2012
: Decentralized Training over Decentralized Data H Tang, X Lian, M Yan, C Zhang, J Liu International Conference on Machine Learning, 4848-4856, 2018	139	2018
Communication compression for decentralized training H Tang, S Gan, C Zhang, T Zhang, J Liu arXiv preprint arXiv:1803.06443, 2018	133	2018
Finite-Sample Analysis of Proximal Gradient TD Algorithms B Liu, J Liu, M Ghavamzadeh, S Mahadevan, M Petrik UAI, 2015	122*	2015
Exclusive Feature Learning on Arbitrary Structures via -norm D Kong, R Fujimaki, J Liu, F Nie, C Ding Advances in neural information processing systems, 1655-1663, 2014	91	2014
Accelerating stochastic composition optimization M Wang, J Liu, E Fang Advances in Neural Information Processing Systems 29, 1714-1722, 2016	81	2016
Doublesqueeze: Parallel stochastic gradient descent with double-pass error-compensated compression H Tang, C Yu, X Lian, T Zhang, J Liu International Conference on Machine Learning, 6155-6165, 2019	79	2019
Sparse non-negative tensor factorization using columnwise coordinate descent J Liu, J Liu, P Wonka, J Ye Pattern Recognition 45 (1), 649-656, 2012	76	2012
An Accelerated Randomized Kaczmarz Algorithm J Liu, SJ Wright arXiv:1310.2887, 2013	75	2013

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