109 citations · 565 across the 64 of their papers we have counts for
65 papers
Solution Set Dimensions in Convex Optimization and Primal-Polar Facial Signatures
Jiaming Ma, Defeng Sun
We study the possible dimensions of solution sets in linearly perturbed convex optimization problems and their behavior under convex duality. The dimensions of solution sets and in…
Semidefinite Implementations of the Proximal Point Algorithm and Consequences for Progressive Decoupling in Optimization
Xudong Li, R. Tyrrell Rockafellar, Defeng Sun
The proximal point algorithm for finding a zero of a maximal monotone mapping is the engine that drives augmented Lagrangian methods and various splitting schemes in convex optimiz…
Maximal monotonicity of piecewise polyhedral mappings
Xudong Li, R. Tyrrell Rockafellar, Defeng Sun
Maximal monotone mappings that are piecewise polyhedral arise from subdifferentials of convex functions and saddle functions that are piecewise linear-quadratic and enter into algo…
A Semismooth Newton Augmented Lagrangian Method for Sparse Spectral Risk Optimization
Rufeng Xiao, Rujun Jiang, Xudong Li +1
Empirical risk minimization is a standard and effective paradigm for learning predictive models by minimizing average loss. In high-stakes decision-making, however, an average-loss…
A symmetric Gauss-Seidel based alternating proximal ALM for generalized Nash Equilibrium problems in Banach spaces
Defeng Sun, Hailing Wang, Wei Zhao
In this paper, we study a class of monotone generalized Nash equilibrium problems (GNEPs) with jointly linear constraints. The players' strategy spaces are real Hilbert spaces, whi…
A Level Set Method with Secant Iterations for the Least-Squares Constrained Nuclear Norm Minimization
Chiyu Ma, Jiaming Ma, Defeng Sun
We present an efficient algorithm for least-squares constrained nuclear norm minimization, a computationally challenging problem with broad applications. Our approach combines a le…