Zhaosong Lu


Zhaosong Lu

Professor, Department of Industrial and Systems Engineering


Shepherd Labs
Room 491
100 Union St SE
Minneapolis, MN 55455

Ph.D. in Operations Research, 2005
School of Industrial and Systems Engineering, Georgia Institute of Technology

Scientific & Professional Societies

Professor Lu’s research interests include theory and algorithms for continuous optimization, with applications in data analytics, machine learning, statistics, and image processing, among others. He has published extensively in major journals such as SIAM Journal on Optimization, Mathematical Programming, and Mathematics of Operations Research. His research was funded by the NSERC in Canada. Prior to joining the University of Minnesota, he was a Full Professor in the Department of Mathematics at Simon Fraser University. 

Research Interests

Zhaosong Lu's research interest areas include theory and algorithms for continuous optimization, as well as applications in data analytics, machine learning, statistics, etc.

Research Group
Operations Research
Selected Publications

Enhanced Proximal DC Algorithms with Extrapolation for a Class of Structured Nonsmooth DC Minimization. Mathematical Programming, 176(1-2): 369-401, 2019 (with Z. Sun and Z. Zhou).

Sparse Recovery via Partial Regularization: Models, Theory and Algorithms. Mathematics of Operations Research, 43(4): 1290-1316, 2018 (with X. Li).

Generalized Conjugate Gradient Methods for l 1 Regularized Convex Quadratic Programming with Finite Convergence. Mathematics of Operations Research, 43(1): 275-303, 2018 (with X. Chen).

Randomized Block Proximal Damped Newton Method for Composite Self-Concordant Minimization. SIAM Journal on Optimization, 27(3):1910-1942, 2017.

A Randomized Nonmonotone Block Proximal Gradient Method for a Class of Structured Nonlinear Programming. SIAM Journal on Numerical Analysis, 55(6): 2930-2955, 2017 (with L. Xiao).

An Augmented Lagrangian Method for Non-Lipschitz Nonconvex Programming. SIAM Journal on Numerical Analysis, 55(1): 168--193, 2017 (with X. Chen, L. Guo, J. Ye).

Penalty Methods for a Class of Non-Lipschitz Optimization Problems. SIAM Journal on Optimization, 26(3): 1465-1492, 2016 (with X. Chen, T. K. Pong).

An Accelerated Randomized Proximal Coordinate Gradient Method and its Application to Regularized Empirical Risk Minimization. SIAM Journal on Optimization, 25(4): 2244-2273, 2015 (with Q. Lin, L. Xiao).

Fused Multiple Graphical Lasso. SIAM Journal on Optimization, 25(2): 916-943, 2015 (with X. Shen, P. Wonka, S. Yang, J. Ye).

Orthogonal Rank-One Matrix Pursuit for Matrix Completion. SIAM Journal on Scientific Computing, 37(1): A488-A514, 2015 (with W. Fan, M. Lai, Z. Wang, J. Ye).

On the Complexity Analysis of Randomized Block-Coordinate Descent Methods. Mathematical Programming, 152(1): 615-642, 2015 (with L. Xiao).

Iterative Reweighted Minimization Methods for l p Regularized Unconstrained Nonlinear Programming. Mathematical Programming, 147(1-2): 277-307, 2014.

Iterative Hard Thresholding Methods for l 0 Regularized Convex Cone Programming. Mathematical Programming, 147(1-2): 125-154, 2014.

Sparse Approximation via Penalty Decomposition Methods. SIAM Journal on Optimization, 23(4):2448-2478, 2013 (with Y. Zhang).

An Augmented Lagrangian Approach for Sparse Principal Component Analysis. Mathematical Programming, 135:149-193, 2012 (with Y. Zhang).

Convex Optimization Methods for Dimension Reduction and Coefficient Estimation in Multivariate Linear Regression. Mathematical Programming, 131:163-194, 2012 (with R. D.C. Monteiro, M. Yuan).

Primal-Dual First-Order Methods with O(1/∈) Iteration-Complexity for Cone Programming. Mathematical Programming, 126:1-29, 2011 (with G. Lan, R. D.C. Monteiro).

Smooth Optimization Approach for Sparse Covariance Selection. SIAM Journal on Optimization, 19(4):1807-1827, 2009.

Dimension Reduction and Coefficient Estimation in the Multivariate Linear Regression. Journal of the Royal Statistical Society, Series B (Statistical Methodology), 69(3):329-346, 2007 (with A. Ekici, R. D.C. Monteiro, M. Yuan).

Large-Scale Semidefinite Programming via Saddle Point Mirror-Prox Algorithm. Mathematical Programming, 109(2):211-237, 2007 (with R. D.C. Monteiro, A. S. Nemirovski).

Error Bounds and Limiting Behavior of Weighted Paths Associated with the SDP Map X 1/2 SX 1/2. SIAM Journal on Optimization, 15(2):348-374, 2004 (with R. D.C. Monteiro).