Shiqian Ma

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Donald GoldfarbColumbia UniversityVerified email at columbia.edu
Shuzhong ZhangProfessor of Industrial and Systems Engineering, University of MinnesotaVerified email at umn.edu
Tianyi LinUniversity of California, BerkeleyVerified email at berkeley.edu
Wei Liu, Fellow of IEEE/IAPR/IMADistinguished Scientist, TencentVerified email at ee.columbia.edu
Katya ScheinbergCornell UniversityVerified email at cornell.edu
Lingzhou XueAssociate Professor of Statistics, The Pennsylvania State UniversityVerified email at psu.edu
Yu-Hong Daichinese academy of sciencesVerified email at lsec.cc.ac.cn
Hui ZouUniversity of MinnesotaVerified email at umn.edu
Junfeng YangNanjing UniversityVerified email at nju.edu.cn
Wotao YinDAMO Academy, Alibaba Group USVerified email at alibaba-inc.com
Amit ChakrabortyHead, Predictive Analytics, Siemens Corporation, Corporate TechnologyVerified email at siemens.com
Anthony Man-Cho SoDepartment of Systems Engineering and Engineering Management, The Chinese University of Hong KongVerified email at se.cuhk.edu.hk
Zhi-Quan LuoProfessor, The Chinese University of Hong Kong, Shenzhen, ChinaVerified email at cuhk.edu.cn
Mingyi HongAssociate Professor, University of MinnesotaVerified email at umn.edu
Meisam RazaviyaynUniversity of Southern CaliforniaVerified email at usc.edu
Minhui HuangResearch ScientistVerified email at meta.com
Ya-Feng Liu (刘亚锋)Associate Professor of Academy of Mathematics and Systems Science, Chinese Academy of SciencesVerified email at lsec.cc.ac.cn
Tong ZhangHKUSTVerified email at tongzhang-ml.org
Necdet Serhat AybatIndustrial Engineering, Penn State UniversityVerified email at psu.edu
Krishnakumar BalasubramanianUniversity of California, DavisVerified email at ucdavis.edu

Shiqian Ma

Rice University and UC Davis (on leave)

Verified email at rice.edu - Homepage

Optimization Machine Learning Data Science Operations Research


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Fixed point and Bregman iterative methods for matrix rank minimization S Ma, D Goldfarb, L Chen Mathematical Programming 128 (1-2), 321-353, 2011	1149	2011
An efficient algorithm for compressed MR imaging using total variation and wavelets S Ma, W Yin, Y Zhang, A Chakraborty 2008 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2008	445	2008
Fast alternating linearization methods for minimizing the sum of two convex functions D Goldfarb, S Ma, K Scheinberg Mathematical Programming 141 (1-2), 349-382, 2013	303	2013
Sparse inverse covariance selection via alternating linearization methods K Scheinberg, S Ma, D Goldfarb Advances in neural information processing systems 23, 2010	229	2010
Barzilai-borwein step size for stochastic gradient descent C Tan, S Ma, YH Dai, Y Qian Advances in neural information processing systems 29, 2016	184	2016
On the global linear convergence of the ADMM with multiblock variables T Lin, S Ma, S Zhang SIAM Journal on Optimization 25 (3), 1478-1497, 2015	172	2015
Highly accurate model for prediction of lung nodule malignancy with CT scans JL Causey, J Zhang, S Ma, B Jiang, JA Qualls, DG Politte, F Prior, ... Scientific reports 8 (1), 9286, 2018	170	2018
Convergence of fixed-point continuation algorithms for matrix rank minimization D Goldfarb, S Ma Foundations of Computational Mathematics 11 (2), 183-210, 2011	163	2011
Stochastic quasi-Newton methods for nonconvex stochastic optimization X Wang, S Ma, D Goldfarb, W Liu SIAM Journal on Optimization 27 (2), 927-956, 2017	161	2017
Positive-definite ℓ1-penalized estimation of large covariance matrices L Xue, S Ma, H Zou Journal of the American Statistical Association 107 (500), 1480-1491, 2012	157	2012
Inertial proximal ADMM for linearly constrained separable convex optimization C Chen, RH Chan, S Ma, J Yang SIAM Journal on Imaging Sciences 8 (4), 2239-2267, 2015	145	2015
Structured nonconvex and nonsmooth optimization: algorithms and iteration complexity analysis B Jiang, T Lin, S Ma, S Zhang Computational Optimization and Applications 72 (1), 115-157, 2019	132	2019
Distributed linearized alternating direction method of multipliers for composite convex consensus optimization NS Aybat, Z Wang, T Lin, S Ma IEEE Transactions on Automatic Control 63 (1), 5-20, 2017	127	2017
Alternating direction methods for latent variable Gaussian graphical model selection S Ma, L Xue, H Zou Neural computation 25 (8), 2172-2198, 2013	123	2013
Fast multiple-splitting algorithms for convex optimization D Goldfarb, S Ma SIAM Journal on Optimization 22 (2), 533-556, 2012	122	2012
On the sublinear convergence rate of multi-block ADMM TY Lin, SQ Ma, SZ Zhang Journal of the Operations Research Society of China 3, 251-274, 2015	119*	2015
Proximal gradient method for nonsmooth optimization over the Stiefel manifold S Chen, S Ma, A Man-Cho So, T Zhang SIAM Journal on Optimization 30 (1), 210-239, 2020	98*	2020
Solving multiple-block separable convex minimization problems using two-block alternating direction method of multipliers X Wang, M Hong, S Ma, ZQ Luo Pacific Journal of Optimization 11 (4), 645-667, 2013	96	2013
A general inertial proximal point algorithm for mixed variational inequality problem C Chen, S Ma, J Yang SIAM Journal on Optimization 25 (4), 2120-2142, 2015	90	2015
A block successive upper-bound minimization method of multipliers for linearly constrained convex optimization M Hong, TH Chang, X Wang, M Razaviyayn, S Ma, ZQ Luo Mathematics of Operations Research 45 (3), 833-861, 2020	87	2020

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