Mahmoud (Mido) Assran
Mahmoud (Mido) Assran
PhD student at McGill University; Mila
Verified email at mail.mcgill.ca - Homepage
Title
Cited by
Cited by
Year
Stochastic gradient push for distributed deep learning
M Assran, N Loizou, N Ballas, M Rabbat
ICML - International Conference on Machine Learning 97, 344-353, 2019
1402019
Asynchronous gradient-push
M Assran, M Rabbat
IEEE Transactions on Automatic Control 66 (1), 168-183, 2021
39*2021
On the convergence of Nesterov's accelerated gradient method in stochastic settings
M Assran, M Rabbat
ICML - International Conference on Machine Learning 119, 410-420, 2020
202020
Gossip-based actor-learner architectures for deep reinforcement learning
M Assran, J Romoff, N Ballas, J Pineau, M Rabbat
NeurIPS - Advances in Neural Information Processing Systems 32, 13320-13330, 2019
152019
An empirical comparison of multi-agent optimization algorithms
M Assran, M Rabbat
IEEE GlobalSIP - IEEE Global Conference on Signal and Information Processing, 2017
132017
Advances in asynchronous parallel and distributed optimization
M Assran, A Aytekin, H Feyzmahdavian, M Johansson, M Rabbat
Proceedings of the IEEE 108 (11), 2013-2031, 2020
112020
Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples
M Assran, M Caron, I Misra, P Bojanowski, A Joulin, N Ballas, M Rabbat
ICCV - IEEE/CVF International Conference on Computer Vision, 8443-8452, 2021
52021
Supervision Accelerates Pre-training in Contrastive Semi-Supervised Learning of Visual Representations
M Assran, N Ballas, L Castrejon, M Rabbat
NeurIPS - Workshop on Self-Supervised Learning, 2020
4*2020
Asynchronous subgradient push: Fast, robust, and scalable multi-agent optimization
M Assran
McGill University Libraries, 2018
32018
A Closer Look at Codistillation for Distributed Training
S Sodhani, O Delalleau, M Assran, K Sinha, N Ballas, M Rabbat
arXiv preprint arXiv:2010.02838, 2020
12020
Memory Augmented Optimizers for Deep Learning
PA McRae, P Parthasarathi, M Assran, S Chandar
arXiv preprint arXiv:2106.10708, 2021
2021
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