35 citations · 107 across the 26 of their papers we have counts for
Showing 2020Show all
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stat.ML2020★ 10 cited
Faster Non-Convex Federated Learning via Global and Local Momentum
Rudrajit Das, Anish Acharya, Abolfazl Hashemi +3
We propose \texttt{FedGLOMO}, a novel federated learning (FL) algorithm with an iteration complexity of to converge to an -stationary point (i.e., $\math…
cs.LG2020★ 5 cited
On the Benefits of Multiple Gossip Steps in Communication-Constrained Decentralized Optimization
Abolfazl Hashemi, Anish Acharya, Rudrajit Das +3
In decentralized optimization, it is common algorithmic practice to have nodes interleave (local) gradient descent iterations with gossip (i.e. averaging over the network) steps. M…
eess.SY2020★ 3 cited
Decentralized Optimization On Time-Varying Directed Graphs Under Communication Constraints
Yiyue Chen, Abolfazl Hashemi, Haris Vikalo
We consider the problem of decentralized optimization where a collection of agents, each having access to a local cost function, communicate over a time-varying directed network an…