295 citations · 405 across the 47 of their papers we have counts for
6 papers · 1 filter
Random Orthogonalization for Federated Learning in Massive MIMO Systems
Xizixiang Wei, Cong Shen, Jing Yang +1
We propose a novel communication design, termed random orthogonalization, for federated learning (FL) in a massive multiple-input and multiple-output (MIMO) wireless system. The ke…
A Self-Play Posterior Sampling Algorithm for Zero-Sum Markov Games
Wei Xiong, Han Zhong, Chengshuai Shi +2
Existing studies on provably efficient algorithms for Markov games (MGs) almost exclusively build on the "optimism in the face of uncertainty" (OFU) principle. This work focuses on…
Nearly Minimax Optimal Offline Reinforcement Learning with Linear Function Approximation: Single-Agent MDP and Markov Game
Wei Xiong, Han Zhong, Chengshuai Shi +3
Offline reinforcement learning (RL) aims at learning an optimal strategy using a pre-collected dataset without further interactions with the environment. While various algorithms h…
On Top- Selection from -wise Partial Rankings via Borda Counting
Wenjing Chen, Ruida Zhou, Chao Tian +1
We analyze the performance of the Borda counting algorithm in a non-parametric model. The algorithm needs to utilize probabilistic rankings of the items within -sized subsets to…
On Federated Learning with Energy Harvesting Clients
Cong Shen, Jing Yang, Jie Xu
Catering to the proliferation of Internet of Things devices and distributed machine learning at the edge, we propose an energy harvesting federated learning (EHFL) framework in thi…
Random Orthogonalization for Federated Learning in Massive MIMO Systems
Xizixiang Wei, Cong Shen, Jing Yang +1
We propose a novel uplink communication method, coined random orthogonalization, for federated learning (FL) in a massive multiple-input and multiple-output (MIMO) wireless system.…