27 citations · 101 across the 25 of their papers we have counts for
4 papers · 1 filter
Tackling Data Heterogeneity: A New Unified Framework for Decentralized SGD with Sample-induced Topology
Yan Huang, Ying Sun, Zehan Zhu +2
We develop a general framework unifying several gradient-based stochastic optimization methods for empirical risk minimization problems both in centralized and distributed scenario…
A Unified Contraction Analysis of a Class of Distributed Algorithms for Composite Optimization
Jinming Xu, Ying Sun, Ye Tian +1
We study distributed composite optimization over networks: agents minimize the sum of a smooth (strongly) convex function, the agents' sum-utility, plus a non-smooth (extended-valu…
Accelerated Primal-Dual Algorithms for Distributed Smooth Convex Optimization over Networks
Jinming Xu, Ye Tian, Ying Sun +1
This paper proposes a novel family of primal-dual-based distributed algorithms for smooth, convex, multi-agent optimization over networks that uses only gradient information and go…
Asynchronous Decentralized Successive Convex Approximation
Ye Tian, Ying Sun, Gesualdo Scutari
We study decentralized asynchronous multiagent optimization over networks, modeled as static (possibly directed) graphs. The optimization problem consists of minimizing a (possibly…