Synthetic data shuffling accelerates the convergence of federated learning under data heterogeneity

Bo Li, Yasin Esfandiari, Mikkel N. Schmidt +2

In federated learning, data heterogeneity is a critical challenge. A straightforward solution is to shuffle the clients' data to homogenize the distribution. However, this may viol…