489 citations · 810 across the 17 of their papers we have counts for
19 papers
Masked Siamese Networks for Label-Efficient Learning
Mahmoud Assran, Mathilde Caron, Ishan Misra +6
We propose Masked Siamese Networks (MSN), a self-supervised learning framework for learning image representations. Our approach matches the representation of an image view containi…
Accounting for Variance in Machine Learning Benchmarks
Xavier Bouthillier, Pierre Delaunay, Mirko Bronzi +14
Strong empirical evidence that one machine-learning algorithm A outperforms another one B ideally calls for multiple trials optimizing the learning pipeline over sources of variati…
Online Adversarial Attacks
Andjela Mladenovic, Avishek Joey Bose, Hugo Berard +4
Adversarial attacks expose important vulnerabilities of deep learning models, yet little attention has been paid to settings where data arrives as a stream. In this paper, we forma…
Efficient Learning in Non-Stationary Linear Markov Decision Processes
Ahmed Touati, Pascal Vincent
We study episodic reinforcement learning in non-stationary linear (a.k.a. low-rank) Markov Decision Processes (MDPs), i.e, both the reward and transition kernel are linear with res…
Implicit Regularization via Neural Feature Alignment
Aristide Baratin, Thomas George, César Laurent +4
We approach the problem of implicit regularization in deep learning from a geometrical viewpoint. We highlight a regularization effect induced by a dynamical alignment of the neura…
Stochastic Hamiltonian Gradient Methods for Smooth Games
Nicolas Loizou, Hugo Berard, Alexia Jolicoeur-Martineau +3
The success of adversarial formulations in machine learning has brought renewed motivation for smooth games. In this work, we focus on the class of stochastic Hamiltonian methods a…