Minibatch vs Local SGD for Heterogeneous Distributed Learning

8 Jun 2020Blake WoodworthKumar Kshitij PatelNathan Srebro

We analyze Local SGD (aka parallel or federated SGD) and Minibatch SGD in the heterogeneous distributed setting, where each machine has access to stochastic gradient estimates for a different, machine-specific, convex objective; the goal is to optimize w.r.t. the average objective; and machines can only communicate intermittently... (read more)

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