1 citations · 1 across the 5 of their papers we have counts for
5 papers
Accelerating Low-Rank Factorization-Based Semidefinite Programming Algorithms on GPU
Qiushi Han, Zhenwei Lin, Hanwen Liu +4
In this paper, we address a long-standing challenge: how to achieve both efficiency and scalability in solving semidefinite programming problems. We propose breakthrough accelerati…
A Low-Rank ADMM Splitting Approach for Semidefinite Programming
Qiushi Han, Chenxi Li, Zhenwei Lin +5
We introduce a new first-order method for solving general semidefinite programming problems, based on the alternating direction method of multipliers (ADMM) and a matrix-splitting…
Trust Region Methods For Nonconvex Stochastic Optimization Beyond Lipschitz Smoothness
Chenghan Xie, Chenxi Li, Chuwen Zhang +3
In many important machine learning applications, the standard assumption of having a globally Lipschitz continuous gradient may fail to hold. This paper delves into a more general…
First-order methods for Stochastic Variational Inequality problems with Function Constraints
Digvijay Boob, Qi Deng, Mohammad Khalafi
The monotone Variational Inequality (VI) is a general model with important applications in various engineering and scientific domains. In numerous instances, the VI problems are ac…
Stochastic Dimension-reduced Second-order Methods for Policy Optimization
Jinsong Liu, Chenghan Xie, Qi Deng +2
In this paper, we propose several new stochastic second-order algorithms for policy optimization that only require gradient and Hessian-vector product in each iteration, making the…