Convergence Analysis of the Last Iterate in Distributed Stochastic Gradient Descent with Momentum

Difei Cheng, Ruinan Jin, Hong Qiao +1

Distributed stochastic gradient methods are widely used to preserve data privacy and ensure scalability in large-scale learning tasks. While existing theory on distributed momentum…