activity
20192022
most citedOn Solving Minimax Optimization Locally: A Follow-the-Ridge Approach

18 citations · 29 across the 4 of their papers we have counts for

collaborators

8 papers

cs.LG2022

Learning Rationalizable Equilibria in Multiplayer Games

Yuanhao Wang, Dingwen Kong, Yu Bai +1

A natural goal in multiagent learning besides finding equilibria is to learn rationalizable behavior, where players learn to avoid iteratively dominated actions. However, even in t…

cs.LG202111 cited

V-Learning -- A Simple, Efficient, Decentralized Algorithm for Multiagent RL

Chi Jin, Qinghua Liu, Yuanhao Wang +1

A major challenge of multiagent reinforcement learning (MARL) is the curse of multiagents, where the size of the joint action space scales exponentially with the number of agents.…

cs.LG2021

An Exponential Lower Bound for Linearly-Realizable MDPs with Constant Suboptimality Gap

Yuanhao Wang, Ruosong Wang, Sham M. Kakade

A fundamental question in the theory of reinforcement learning is: suppose the optimal -function lies in the linear span of a given dimensional feature mapping, is sample-ef…

cs.LG2020

Refined Analysis of FPL for Adversarial Markov Decision Processes

Yuanhao Wang, Kefan Dong

We consider the adversarial Markov Decision Process (MDP) problem, where the rewards for the MDP can be adversarially chosen, and the transition function can be either known or unk…

math.OC2020

On the Suboptimality of Negative Momentum for Minimax Optimization

Guodong Zhang, Yuanhao Wang

Smooth game optimization has recently attracted great interest in machine learning as it generalizes the single-objective optimization paradigm. However, game dynamics is more comp…

cs.LG2020

Improved Algorithms for Convex-Concave Minimax Optimization

Yuanhao Wang, Jian Li

This paper studies minimax optimization problems , where is -strongly convex with respect to , -strongly concave with respect to and…