From Mixing to Tearing: Graph Decomposition in Decentralized Optimization via Message Passing
Paper recorded by Signals 4 on 2026-10-02 in cs.LG. Abstract reproduced from arXiv; link to the original below.
Published 2026-10-02 on arXiv · recorded by Signals 4 on 2026-10-05
Category: cs.LG · 机器学习 · first seen 2026-10-05
Abstract
We study the minimization of sums of smooth strongly convex functions over undirected graphs, with each function held by one agent and communication restricted to neighbors in the graph. Existing decentralized methods, whether based on gossip or on routing over spanning trees, typically
use the network to mix or aggregate information to enable
{\it prescribed} local optimization
updates. Wha
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Cite this page: From Mixing to Tearing: Graph Decomposition in Decentralized Optimization via Message Passing: the #384 most recent of 762 cs.LG papers we have recorded (as of 2026-10-02). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/from-mixing-to-tearing-graph-decomposition-in-decentralized-optimization-via-mes.html
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