23 citations · 93 across the 8 of their papers we have counts for
7 papers · 1 filter
Finite-Sample Analysis For Decentralized Batch Multi-Agent Reinforcement Learning With Networked Agents
Kaiqing Zhang, Zhuoran Yang, Han Liu +2
Despite the increasing interest in multi-agent reinforcement learning (MARL) in multiple communities, understanding its theoretical foundation has long been recognized as a challen…
A convex formulation for high-dimensional sparse sliced inverse regression
Kean Ming Tan, Zhaoran Wang, Tong Zhang +2
Sliced inverse regression is a popular tool for sufficient dimension reduction, which replaces covariates with a minimal set of their linear combinations without loss of informatio…
Adaptive Sampling Towards Fast Graph Representation Learning
Wenbing Huang, Tong Zhang, Yu Rong +1
Graph Convolutional Networks (GCNs) have become a crucial tool on learning representations of graph vertices. The main challenge of adapting GCNs on large-scale graphs is the scala…
Diffusion Approximations for Online Principal Component Estimation and Global Convergence
Chris Junchi Li, Mengdi Wang, Han Liu +1
In this paper, we propose to adopt the diffusion approximation tools to study the dynamics of Oja's iteration which is an online stochastic gradient descent method for the principa…
Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization
Jiaxiang Wu, Weidong Huang, Junzhou Huang +1
Large-scale distributed optimization is of great importance in various applications. For data-parallel based distributed learning, the inter-node gradient communication often becom…
Fully Decentralized Multi-Agent Reinforcement Learning with Networked Agents
Kaiqing Zhang, Zhuoran Yang, Han Liu +2
We consider the problem of \emph{fully decentralized} multi-agent reinforcement learning (MARL), where the agents are located at the nodes of a time-varying communication network.…