28 citations · 48 across the 3 of their papers we have counts for
4 papers
Communication-efficient SGD: From Local SGD to One-Shot Averaging
Artin Spiridonoff, Alex Olshevsky, Ioannis Ch. Paschalidis
We consider speeding up stochastic gradient descent (SGD) by parallelizing it across multiple workers. We assume the same data set is shared among workers, who can take SGD ste…
Local SGD With a Communication Overhead Depending Only on the Number of Workers
Artin Spiridonoff, Alex Olshevsky, Ioannis Ch. Paschalidis
We consider speeding up stochastic gradient descent (SGD) by parallelizing it across multiple workers. We assume the same data set is shared among workers, who can take SGD ste…
Robust Asynchronous Stochastic Gradient-Push: Asymptotically Optimal and Network-Independent Performance for Strongly Convex Functions
Artin Spiridonoff, Alex Olshevsky, Ioannis Ch. Paschalidis
We consider the standard model of distributed optimization of a sum of functions $F(\bz) = \sum_{i=1}^n f_i(\bz)$, where node in a network holds the function $f_i(\bz)$. We all…
Fully Asynchronous Push-Sum With Growing Intercommunication Intervals
Alex Olshevsky, Ioannis Ch. Paschalidis, Artin Spiridonoff
We propose an algorithm for average consensus over a directed graph which is both fully asynchronous and robust to unreliable communications. We show its convergence to the average…