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.
February 15, 2024
Adrien Bardes, Quentin Garrido, Xinlei Chen, Michael Rabbat, Yann LeCun, Mido Assran, Nicolas Ballas, Jean Ponce
February 15, 2024
June 18, 2023
Mido Assran, Quentin Duval, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Mike Rabbat, Yann LeCun, Nicolas Ballas
June 18, 2023
September 16, 2020
Mike Rabbat, Mido Assran, Arda Aytekin, Hamid Feyzmahdavian, Mikael Johansson
September 16, 2020
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Foundational models