Mahmoud Assran

According to our database, Mahmoud Assran authored at least 19 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Modeling Caption Diversity in Contrastive Vision-Language Pretraining.

Samuel Lavoie, Polina Kirichenko, Mark Ibrahim, Mahmoud Assran, Andrew Gordon Wilson, Aaron C. Courville, Nicolas Ballas

CoRR, 2024

Revisiting Feature Prediction for Learning Visual Representations from Video.

Adrien Bardes, Quentin Garrido, Jean Ponce, Xinlei Chen, Michael G. Rabbat, Yann LeCun, Mahmoud Assran, Nicolas Ballas

CoRR, 2024

Learning and Leveraging World Models in Visual Representation Learning.

Quentin Garrido, Mahmoud Assran, Nicolas Ballas, Adrien Bardes, Laurent Najman, Yann LeCun

CoRR, 2024

2023

Predicting masked tokens in stochastic locations improves masked image modeling.

Amir Bar, Florian Bordes, Assaf Shocher, Mahmoud Assran, Pascal Vincent, Nicolas Ballas, Trevor Darrell, Amir Globerson, Yann LeCun

CoRR, 2023

DINOv2: Learning Robust Visual Features without Supervision.

Maxime Oquab, Timothée Darcet, Théo Moutakanni, Huy Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel Haziza, Francisco Massa, Alaaeldin El-Nouby, Mahmoud Assran, Nicolas Ballas, Wojciech Galuba, Russell Howes, Po-Yao Huang, Shang-Wen Li, Ishan Misra, Michael G. Rabbat, Vasu Sharma, Gabriel Synnaeve, Hu Xu, Hervé Jégou, Julien Mairal, Patrick Labatut, Armand Joulin, Piotr Bojanowski

CoRR, 2023

Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture.

Mahmoud Assran, Quentin Duval, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Yann LeCun, Nicolas Ballas

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

The Hidden Uniform Cluster Prior in Self-Supervised Learning.

Mahmoud Assran, Randall Balestriero, Quentin Duval, Florian Bordes, Ishan Misra, Piotr Bojanowski, Pascal Vincent, Michael G. Rabbat, Nicolas Ballas

CoRR, 2022

Masked Siamese Networks for Label-Efficient Learning.

Mahmoud Assran, Mathilde Caron, Ishan Misra, Piotr Bojanowski, Florian Bordes, Pascal Vincent, Armand Joulin, Mike Rabbat, Nicolas Ballas

Proceedings of the Computer Vision - ECCV 2022, 2022

2021

Asynchronous Gradient Push.

Mahmoud Assran, Michael G. Rabbat

IEEE Trans. Autom. Control., 2021

Memory Augmented Optimizers for Deep Learning.

Paul-Aymeric McRae, Prasanna Parthasarathi, Mahmoud Assran, Sarath Chandar

CoRR, 2021

Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples.

Mahmoud Assran, Mathilde Caron, Ishan Misra, Piotr Bojanowski, Armand Joulin, Nicolas Ballas, Michael G. Rabbat

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020

Advances in Asynchronous Parallel and Distributed Optimization.

Mahmoud Assran, Arda Aytekin, Hamid Reza Feyzmahdavian, Mikael Johansson, Michael G. Rabbat

Proc. IEEE, 2020

A Closer Look at Codistillation for Distributed Training.

Shagun Sodhani, Olivier Delalleau, Mahmoud Assran, Koustuv Sinha, Nicolas Ballas, Michael G. Rabbat

CoRR, 2020

Recovering Petaflops in Contrastive Semi-Supervised Learning of Visual Representations.

Mahmoud Assran, Nicolas Ballas, Lluís Castrejón, Michael G. Rabbat

CoRR, 2020

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

Mahmoud Assran, Mike Rabbat

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning.

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

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Stochastic Gradient Push for Distributed Deep Learning.

Mahmoud Assran, Nicolas Loizou, Nicolas Ballas, Michael G. Rabbat

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Asynchronous Subgradient-Push.

Mahmoud Assran, Michael G. Rabbat

CoRR, 2018

2017

An empirical comparison of multi-agent optimization algorithms.

Mahmoud Assran, Michael G. Rabbat

Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing, 2017