Mido Assran

Montreal, Canada

Mido is a researcher at Facebook AI Research (FAIR) and Mila – Quebec AI Institute. He is an NSERC Vanier Scholar and holds a Vadasz Doctoral Fellowship in Engineering at McGill University. His research focuses on developing machine learning algorithms, with an emphasis on the data-/time-/energy-efficiency of learning. He is interested in optimization, distributed computing, and self-/semi-/weakly-supervised learning. His previous work has spanned both large-scale empirical analyses and theoretical studies.

Mido's Work

Mido's Publications

August 14, 2020

RESEARCH

On the Convergence of Nesterov’s Accelerated Gradient Method in Stochastic Settings

Mido Assran, Michael Rabbat

August 14, 2020

January 01, 2021

RESEARCH

Asynchronous Gradient-Push

Mahmoud Assran, Michael Rabbat

January 01, 2021

December 09, 2019

RESEARCH

Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning

Mahmoud Assran, Joshua Romoff, Nicolas Ballas, Joelle Pineau, Michael Rabbat

December 09, 2019