1 citations · 1 across the 7 of their papers we have counts for
7 papers
Personalized Collaborative Learning with Affinity-Based Variance Reduction
Chenyu Zhang, Navid Azizan
Multi-agent learning faces a fundamental tension: leveraging distributed collaboration without sacrificing the personalization needed for diverse agents. This tension intensifies w…
Stochastic Semi-Gradient Descent for Learning Mean Field Games with Population-Aware Function Approximation
Chenyu Zhang, Xu Chen, Xuan Di
Mean field games (MFGs) model interactions in large-population multi-agent systems through population distributions. Traditional learning methods for MFGs are based on fixed-point…
Graphon Mean Field Games with a Representative Player: Analysis and Learning Algorithm
Fuzhong Zhou, Chenyu Zhang, Xu Chen +1
We propose a discrete time graphon game formulation on continuous state and action spaces using a representative player to study stochastic games with heterogeneous interaction amo…
A Single Online Agent Can Efficiently Learn Mean Field Games
Chenyu Zhang, Xu Chen, Xuan Di
Mean field games (MFGs) are a promising framework for modeling the behavior of large-population systems. However, solving MFGs can be challenging due to the coupling of forward pop…
Finite-Time Analysis of On-Policy Heterogeneous Federated Reinforcement Learning
Chenyu Zhang, Han Wang, Aritra Mitra +1
Federated reinforcement learning (FRL) has emerged as a promising paradigm for reducing the sample complexity of reinforcement learning tasks by exploiting information from differe…
Riemannian Adaptive Regularized Newton Methods with Hölder Continuous Hessians
Chenyu Zhang, Rujun Jiang
This paper presents strong worst-case iteration and operation complexity guarantees for Riemannian adaptive regularized Newton methods, a unified framework encompassing both Rieman…
Riemannian Trust Region Methods for SC Minimization
Chenyu Zhang, Rufeng Xiao, Wen Huang +1
Manifold optimization has recently gained significant attention due to its wide range of applications in various areas. This paper introduces the first Riemannian trust region meth…