2 citations · 2 across the 2 of their papers we have counts for
5 papers
Asynchronous Gradient Play in Zero-Sum Multi-agent Games
Ruicheng Ao, Shicong Cen, Yuejie Chi
Finding equilibria via gradient play in competitive multi-agent games has been attracting a growing amount of attention in recent years, with emphasis on designing efficient strate…
Faster Last-iterate Convergence of Policy Optimization in Zero-Sum Markov Games
Shicong Cen, Yuejie Chi, Simon S. Du +1
Multi-Agent Reinforcement Learning (MARL) -- where multiple agents learn to interact in a shared dynamic environment -- permeates across a wide range of critical applications. Whil…
Communication-Efficient Distributed Optimization in Networks with Gradient Tracking and Variance Reduction
Boyue Li, Shicong Cen, Yuxin Chen +1
There is growing interest in large-scale machine learning and optimization over decentralized networks, e.g. in the context of multi-agent learning and federated learning. Due to t…
Convergence of Distributed Stochastic Variance Reduced Methods without Sampling Extra Data
Shicong Cen, Huishuai Zhang, Yuejie Chi +2
Stochastic variance reduced methods have gained a lot of interest recently for empirical risk minimization due to its appealing run time complexity. When the data size is large and…
A Stochastic Semismooth Newton Method for Nonsmooth Nonconvex Optimization
Andre Milzarek, Xiantao Xiao, Shicong Cen +2
In this work, we present a globalized stochastic semismooth Newton method for solving stochastic optimization problems involving smooth nonconvex and nonsmooth convex terms in the…