6 papers
A Line-search-free Method for Adaptive Decentralized Optimization
Xiaokai Chen, Ilya Kuruzov, Gesualdo Scutari
We study decentralized optimization over networks where agents cooperatively minimize a smooth (strongly) convex sum of local losses while communicating only with immediate neighbo…
Adaptive Decentralized Composite Optimization via Three-Operator Splitting
Xiaokai Chen, Ilya Kuruzov, Gesualdo Scutari
The paper studies decentralized optimization over networks, where agents minimize a sum of {\it locally} smooth (strongly) convex losses and plus a nonsmooth convex extended value…
A Parameter-free Decentralized Algorithm for Composite Convex Optimization
Xiaokai Chen, Ilya Kuruzov, Gesualdo Scutari +1
The paper studies decentralized optimization over networks, where agents minimize a composite objective consisting of the sum of smooth convex functions--the agents' losses--and an…
Adaptive Stepsize Selection in Decentralized Convex Optimization
Ilya Kuruzov, Xiaokai Chen, Gesualdo Scutari +1
We study decentralized optimization where multiple agents minimize the average of their (strongly) convex, smooth losses over a communication graph. Convergence of the existing dec…
DCatalyst: A Unified Accelerated Framework for Decentralized Optimization
Tianyu Cao, Xiaokai Chen, Gesualdo Scutari
We study decentralized optimization over a network of agents, modeled as graphs, with no central server. The goal is to minimize , where represents a (strongly) convex fun…
Enhancing Convergence of Decentralized Gradient Tracking under the KL Property
Xiaokai Chen, Tianyu Cao, Gesualdo Scutari
We study decentralized multiagent optimization over networks, modeled as undirected graphs. The optimization problem consists of minimizing a nonconvex smooth function plus a conve…