8 citations · 16 across the 7 of their papers we have counts for
7 papers
UGM: A Unified Framework and New Perspectives for Accelerated Gradient Methods in Smooth and Strongly Convex Optimization
Danqing Zhou, Shiqian Ma, Junfeng Yang
In this paper, we propose a unified framework for accelerated gradient methods, dubbed UGM, which subsumes a wide range of accelerated and conventional gradient-type methods design…
On the Convergence of Constrained Gradient Method
Danqing Zhou, Hongmei Chen, Shiqian Ma +1
The constrained gradient method (CGM) has recently been proposed to solve convex optimization and monotone variational inequality (VI) problems with general functional constraints.…
A Simple Adaptive Proximal Gradient Method for Nonconvex Optimization
Zilong Ye, Shiqian Ma, Junfeng Yang +1
Consider composite nonconvex optimization problems where the objective function consists of a smooth nonconvex term (with Lipschitz-continuous gradient) and a convex (possibly nons…
Relaxed Proximal Point Algorithm: Tight Complexity Bounds and Acceleration without Momentum
Bofan Wang, Shiqian Ma, Junfeng Yang +1
In this paper, we focus on the relaxed proximal point algorithm (RPPA) for solving convex (possibly nonsmooth) optimization problems. We conduct a comprehensive study on three type…
Applications of gauge duality in robust principal component analysis and semidefinite programming
Shiqian Ma, Junfeng Yang
Gauge duality theory was originated by Freund [Math. Programming, 38(1):47-67, 1987] and was recently further investigated by Friedlander, Mac{ê}do and Pong [SIAM J. Optm., 24(4):1…
Inertial primal-dual algorithms for structured convex optimization
Raymond H. Chan, Shiqian Ma, Junfeng Yang
The primal-dual algorithm recently proposed by Chambolle & Pock (abbreviated as CPA) for structured convex optimization is very efficient and popular. It was shown by Chambolle & P…
A general inertial proximal point method for mixed variational inequality problem
Caihua Chen, Shiqian Ma, Junfeng Yang
In this paper, we first propose a general inertial proximal point method for the mixed variational inequality (VI) problem. Based on our knowledge, without stronger assumptions, co…