10 citations · 12 across the 9 of their papers we have counts for
4 papers · 1 filter
A Zeroth-Order Variance-Reduced Method for Decentralized Stochastic Non-convex Optimization
Hongxu Chen, Jinchi Chen, Ke Wei
In this paper, we consider a distributed stochastic non-convex optimization problem, which is about minimizing a sum of local cost functions over a network with only zeroth-ord…
On the Linear Convergence of Policy Gradient under Hadamard Parameterization
Jiacai Liu, Jinchi Chen, Ke Wei
The convergence of deterministic policy gradient under the Hadamard parameterization is studied in the tabular setting and the linear convergence of the algorithm is established. T…
Decentralized Natural Policy Gradient with Variance Reduction for Collaborative Multi-Agent Reinforcement Learning
Jinchi Chen, Jie Feng, Weiguo Gao +1
This paper studies a policy optimization problem arising from collaborative multi-agent reinforcement learning in a decentralized setting where agents communicate with their neighb…
Implicit Regularization and Entrywise Convergence of Riemannian Optimization for Low Tucker-Rank Tensor Completion
Haifeng Wang, Jinchi Chen, Ke Wei
This paper is concerned with the low Tucker-rank tensor completion problem, which is about reconstructing a tensor of low multilinear rank f…