Erick Lavoie

Refined Convergence and Topology Learning for Decentralized SGD with Heterogeneous Data

One of the key challenges in decentralized and federated learning is to design algorithms that efficiently deal with highly heterogeneous data distributions across agents. In this paper, we revisit the analysis of Decentralized Stochastic Gradient Descent algorithm (D-SGD) under data heterogeneity.…