Shiqian Ma

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Donald GoldfarbColumbia UniversityVerified email at columbia.edu
Shuzhong ZhangUniversity of MinnesotaVerified email at umn.edu
Tianyi LinColumbia UniversityVerified email at columbia.edu
Katya ScheinbergCornell UniversityVerified email at cornell.edu
Lingzhou XueProfessor of Statistics, The Pennsylvania State UniversityVerified email at psu.edu
Wei Liu, IEEE/IAPR/IMA FellowDistinguished Scientist, TencentVerified email at ee.columbia.edu
Shixiang ChenUniversity of Science and Technology of ChinaVerified email at ustc.edu.cn
Junfeng YangNanjing UniversityVerified email at nju.edu.cn
Minhui HuangResearch ScientistVerified email at meta.com
Yu-Hong Daichinese academy of sciencesVerified email at lsec.cc.ac.cn
Anthony Man-Cho SoDepartment of Systems Engineering and Engineering Management, The Chinese University of Hong KongVerified email at se.cuhk.edu.hk
Hui ZouUniversity of MinnesotaVerified email at umn.edu
Wotao YinDAMO Academy, Alibaba Group USVerified email at alibaba-inc.com
Amit ChakrabortyHead, Predictive Analytics, Siemens Corporation, Corporate TechnologyVerified email at siemens.com
Tong ZhangUIUCVerified email at tongzhang-ml.org
Mingyi HongAssociate Professor, University of Minnesota; Amazon ScholarVerified email at umn.edu
Krishnakumar BalasubramanianUniversity of California, DavisVerified email at ucdavis.edu
Necdet Serhat AybatIndustrial Engineering, Penn State UniversityVerified email at psu.edu
Meisam RazaviyaynUniversity of Southern CaliforniaVerified email at usc.edu
Zhi-Quan LuoProfessor, The Chinese University of Hong Kong, Shenzhen, ChinaVerified email at cuhk.edu.cn

Shiqian Ma

Rice University

Verified email at rice.edu - Homepage

Optimization Machine Learning 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), 321-353, 2011	1233	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	486	2008
Fast alternating linearization methods for minimizing the sum of two convex functions D Goldfarb, S Ma, K Scheinberg Mathematical Programming 141 (1), 349-382, 2013	324	2013
Sparse inverse covariance selection via alternating linearization methods K Scheinberg, S Ma, D Goldfarb Advances in neural information processing systems 23, 2010	252	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	228	2016
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	215	2017
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	208	2018
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	208	2015
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	194	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	187	2015
Convergence of fixed-point continuation algorithms for matrix rank minimization D Goldfarb, S Ma Foundations of Computational Mathematics 11 (2), 183-210, 2011	174	2011
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	159*	2020
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	159	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	152	2017
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	136*	2015
Alternating direction methods for latent variable Gaussian graphical model selection S Ma, L Xue, H Zou Neural computation 25 (8), 2172-2198, 2013	135	2013
Fast multiple-splitting algorithms for convex optimization D Goldfarb, S Ma SIAM Journal on Optimization 22 (2), 533-556, 2012	130	2012
ADMM for high-dimensional sparse penalized quantile regression Y Gu, J Fan, L Kong, S Ma, H Zou Technometrics 60 (3), 319-331, 2018	116	2018
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	115	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	100	2020

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