activity
20172023
most citedStrong Variational Sufficiency for Nonlinear Semidefinite Programming and its Implications

11 citations · 15 across the 7 of their papers we have counts for

collaborators

7 papers

math.OC2023

An Accelerated Proximal Alternating Direction Method of Multipliers for Optimal Decentralized Control of Uncertain Systems

Bo Yang, Xinyuan Zhao, Xudong Li +1

To ensure the system stability of the -guaranteed cost optimal decentralized control problem (ODC), an approximate semidefinite programming (SDP) problem is f…

math.OC2022★ 11 cited

Strong Variational Sufficiency for Nonlinear Semidefinite Programming and its Implications

Shiwei Wang, Chao Ding, Yangjing Zhang +1

Strong variational sufficiency is a newly proposed property, which turns out to be of great use in the convergence analysis of multiplier methods. However, what this property impli…

math.OC2021

A Unified Convergence Analysis of a Second-Order Method of Multipliers for Nonlinear Conic Programming

Liang Chen, Junyuan Zhu, Xinyuan Zhao

In this paper, we accomplish a unified convergence analysis of a second-order method of multipliers (i.e., a second-order augmented Lagrangian method) for solving the conventional…

stat.ML2020

Matrix optimization based Euclidean embedding with outliers

Qian Zhang, Xinyuan Zhao, Chao Ding

Euclidean embedding from noisy observations containing outlier errors is an important and challenging problem in statistics and machine learning. Many existing methods would strugg…

math.OC2019

A proximal DC approach for quadratic assignment problem

Zhuoxuan Jiang, Xinyuan Zhao, Chao Ding

In this paper, we show that the quadratic assignment problem (QAP) can be reformulated to an equivalent rank constrained doubly nonnegative (DNN) problem. Under the framework of th…

math.OC2017★ 3 cited

SDPNAL+: A Matlab software for semidefinite programming with bound constraints (version 1.0)

Defeng Sun, Kim-Chuan Toh, Yancheng Yuan +1

SDPNAL+ is a {\sc Matlab} software package that implements an augmented Lagrangian based method to solve large scale semidefinite programming problems with bound constraints. The i…

math.OC2017★ 1 cited

Quadratic growth conditions for convex matrix optimization problems associated with spectral functions

Ying Cui, Chao Ding, Xinyuan Zhao

In this paper, we provide two types of sufficient conditions for ensuring the quadratic growth conditions of a class of constrained convex symmetric and non-symmetric matrix optimi…