Ji Liu

Cited by

	All	Since 2015
Citations	5655	5146
h-index	35	34
i10-index	64	62

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201120122013201420152016201720182019202036 61 130 237 351 594 660 919 1348 1251

Co-authors

Xiangru LianDepartment of Computer Science, University of RochesterVerified email at ur.rochester.edu
Yang CongState Key Laboratory of Robotics, SIA, Chinese Academy of Sciences (CAS)Verified email at sia.cn
Ce ZhangETH ZurichVerified email at inf.ethz.ch
Jieping Ye, IEEE FellowUniversity of MichiganVerified email at umich.edu
Tong ZhangHKUSTVerified email at tongzhang-ml.org
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
Bo LiuAuburn UniversityVerified email at cs.umass.edu
Haichuan YangUniversity of RochesterVerified email at rochester.edu
Hanlin TangUniversity of RochesterVerified email at ur.rochester.edu
Jiebo LuoProfessor of Computer Science, University of RochesterVerified email at cs.rochester.edu
Junsong YuanState University of New York at BuffaloVerified email at buffalo.edu
Wei ZhangIBM T.J.Watson Research CenterVerified email at us.ibm.com
Sridhar MahadevanDirector, Data Science Lab, Adobe Research & Professor, University of Massachusetts, AmherstVerified email at cs.umass.edu
Przemyslaw MusialskiAssociate Professor of Computer Science, New Jersey Institute of TechnologyVerified email at njit.edu
Cho-Jui HsiehUniversity of California, Los AngelesVerified email at cs.ucla.edu
Chen YuUniversity of Rochester, PhDVerified email at ur.rochester.edu
Shupeng GuiUniversity of RochesterVerified email at ur.rochester.edu
Dan AlistarhIST AustriaVerified email at csail.mit.edu
Christopher RéComputer Science, Stanford UniversityVerified email at cs.stanford.edu

Ji Liu

University of Rochester

Verified email at cs.rochester.edu - Homepage

machine learning optimization reinforcement learning computer vision compressed sensing.


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
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	1089	2013
Sparse reconstruction cost for abnormal event detection Y Cong, J Yuan, J Liu CVPR 2011, 3449-3456, 2011	634	2011
An Asynchronous Parallel Stochastic Coordinate Descent Algorithm J Liu, SJ Wright, C Ré, V Bittorf, S Sridhar arXiv:1311.1873, 2013	322	2013
Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization X Lian, Y Huang, Y Li, J Liu NIPS arXiv preprint arXiv:1506.08272, 2015	279	2015
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 Advances in Neural Information Processing Systems, 5330-5340, 2017	266	2017
Abnormal event detection in crowded scenes using sparse representation Y Cong, J Yuan, J Liu Pattern Recognition 46 (7), 1851-1864, 2013	257	2013
Asynchronous stochastic coordinate descent: Parallelism and convergence properties J Liu, SJ Wright SIAM Journal on Optimization 25 (1), 351-376, 2015	214	2015
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	159	2012
Gradient sparsification for communication-efficient distributed optimization J Wangni, J Wang, J Liu, T Zhang Advances in Neural Information Processing Systems, 1299-1309, 2018	141	2018
Staleness-aware Async-SGD for Distributed Deep Learning W Zhang, S Gupta, X Lian, J Liu IJCAI, arXiv preprint arXiv:1511.05950, 2015	138	2015
Asynchronous decentralized parallel stochastic gradient descent X Lian, W Zhang, C Zhang, J Liu International Conference on Machine Learning, 3043-3052, 2018	120	2018
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	118*	2017
Finite-Sample Analysis of Proximal Gradient TD Algorithms B Liu, J Liu, M Ghavamzadeh, S Mahadevan, M Petrik UAI, 2015	100	2015
D: Decentralized Training over Decentralized Data H Tang, X Lian, M Yan, C Zhang, J Liu arXiv preprint arXiv:1803.07068, 2018	79	2018
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	79	2014
Communication compression for decentralized training H Tang, S Gan, C Zhang, T Zhang, J Liu Advances in Neural Information Processing Systems, 7652-7662, 2018	73*	2018
Sparse non-negative tensor factorization using columnwise coordinate descent J Liu, J Liu, P Wonka, J Ye Pattern Recognition 45 (1), 649-656, 2012	72	2012
Accelerating stochastic composition optimization M Wang, J Liu, EX Fang The Journal of Machine Learning Research 18 (1), 3721-3743, 2017	59	2017
Deep sparse feature selection for computer aided endoscopy diagnosis Y Cong, S Wang, J Liu, J Cao, Y Yang, J Luo Pattern Recognition 48 (3), 907-917, 2015	58	2015
An Accelerated Randomized Kaczmarz Algorithm J Liu, SJ Wright arXiv:1310.2887, 2013	58	2013

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