538 citations · 1.1k across the 31 of their papers we have counts for
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An Effective Anti-Aliasing Approach for Residual Networks
Cristina Vasconcelos, Hugo Larochelle, Vincent Dumoulin +2
Image pre-processing in the frequency domain has traditionally played a vital role in computer vision and was even part of the standard pipeline in the early days of deep learning.…
Beyond variance reduction: Understanding the true impact of baselines on policy optimization
Wesley Chung, Valentin Thomas, Marlos C. Machado +1
Bandit and reinforcement learning (RL) problems can often be framed as optimization problems where the goal is to maximize average performance while having access only to stochasti…
To Each Optimizer a Norm, To Each Norm its Generalization
Sharan Vaswani, Reza Babanezhad, Jose Gallego-Posada +3
We study the implicit regularization of optimization methods for linear models interpolating the training data in the under-parametrized and over-parametrized regimes. Since it is…
An operator view of policy gradient methods
Dibya Ghosh, Marlos C. Machado, Nicolas Le Roux
We cast policy gradient methods as the repeated application of two operators: a policy improvement operator , which maps any policy to a better one ,…
The Geometry of Sign Gradient Descent
Lukas Balles, Fabian Pedregosa, Nicolas Le Roux
Sign-based optimization methods have become popular in machine learning due to their favorable communication cost in distributed optimization and their surprisingly good performanc…