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cs.LG2024
On the Trade-off between Flatness and Optimization in Distributed Learning
Ying Cao, Zhaoxian Wu, Kun Yuan +1
This paper proposes a theoretical framework to evaluate and compare the performance of stochastic gradient algorithms for distributed learning in relation to their behavior around…
cs.LG2024
Asynchronous Diffusion Learning with Agent Subsampling and Local Updates
Elsa Rizk, Kun Yuan, Ali H. Sayed
In this work, we examine a network of agents operating asynchronously, aiming to discover an ideal global model that suits individual local datasets. Our assumption is that each ag…