873 citations · 1.3k across the 35 of their papers we have counts for
6 papers · 1 filter
Dynamic Average Diffusion with randomized Coordinate Updates
Bicheng Ying, Kun Yuan, Ali H. Sayed
This work derives and analyzes an online learning strategy for tracking the average of time-varying distributed signals by relying on randomized coordinate-descent updates. During…
Multi-Agent Fully Decentralized Value Function Learning with Linear Convergence Rates
Lucas Cassano, Kun Yuan, Ali H. Sayed
This work develops a fully decentralized multi-agent algorithm for policy evaluation. The proposed scheme can be applied to two distinct scenarios. In the first scenario, a collect…
A Proximal Diffusion Strategy for Multi-Agent Optimization with Sparse Affine Constraints
Sulaiman A. Alghunaim, Kun Yuan, Ali H. Sayed
This work develops a proximal primal-dual decentralized strategy for multi-agent optimization problems that involve multiple coupled affine constraints, where each constraint may i…
Supervised Learning Under Distributed Features
Bicheng Ying, Kun Yuan, Ali H. Sayed
This work studies the problem of learning under both large datasets and large-dimensional feature space scenarios. The feature information is assumed to be spread across agents in…
Walkman: A Communication-Efficient Random-Walk Algorithm for Decentralized Optimization
Xianghui Mao, Kun Yuan, Yubin Hu +3
This paper addresses consensus optimization problems in a multi-agent network, where all agents collaboratively find a minimizer for the sum of their private functions. We develop…
Stochastic Learning under Random Reshuffling with Constant Step-sizes
Bicheng Ying, Kun Yuan, Stefan Vlaski +1
In empirical risk optimization, it has been observed that stochastic gradient implementations that rely on random reshuffling of the data achieve better performance than implementa…