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math.OC2025
AdGT: Decentralized Gradient Tracking with Adaptive Per-Agent Stepsizes
Diyako Ghaderyan, Stefan Werner
In decentralized optimization, gradient-tracking methods typically rely on a single global stepsize. This choice can be conservative when agents have local objectives with differen…
math.OC2021
A Fast Row-Stochastic Decentralized Method for Distributed Optimization Over Directed Graphs
Diyako Ghaderyan, Necdet Serhat Aybat, A. Pedro Aguiar +1
In this paper, we introduce a fast row-stochastic decentralized algorithm, referred to as FRSD, to solve consensus optimization problems over directed communication graphs. The pro…