438 citations · 1k across the 57 of their papers we have counts for
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Advances in Asynchronous Parallel and Distributed Optimization
Mahmoud Assran, Arda Aytekin, Hamid Feyzmahdavian +2
Motivated by large-scale optimization problems arising in the context of machine learning, there have been several advances in the study of asynchronous parallel and distributed op…
A flexible framework for communication-efficient machine learning: from HPC to IoT
Sarit Khirirat, Sindri Magnússon, Arda Aytekin +1
With the increasing scale of machine learning tasks, it has become essential to reduce the communication between computing nodes. Early work on gradient compression focused on the…
Convergence of a Stochastic Gradient Method with Momentum for Non-Smooth Non-Convex Optimization
Vien V. Mai, Mikael Johansson
Stochastic gradient methods with momentum are widely used in applications and at the core of optimization subroutines in many popular machine learning libraries. However, their sam…