Mila > Team > Nicolas Le Roux

Nicolas Le Roux

Core Industry Member
Adjunct Professor, McGill University, Google, Canada CIFAR AI Chair

I am an academic researcher with expertise in machine learning, computer vision, neural networks, deep learning, optimization, large-scale learning and statistical modeling in general.

Publications

2021-10

ORB-SLAM with Near-infrared images and Optical Flow data
Antonio Buemi, Arcangelo Bruna, Sylvain Petinot and Nicolas Roux
ICCV 2021
(2021-10-01)
openaccess.thecvf.comPDF

2021-08

A functional mirror ascent view of policy gradient methods with function approximation.
Sharan Vaswani, Olivier Bachem, Simone Totaro, Robert Mueller, Matthieu Geist, Marlos C. Machado, Pablo Samuel Castro and Nicolas Le Roux
arXiv preprint arXiv:2108.05828
(2021-08-12)
ui.adsabs.harvard.eduPDF

2021-07

Beyond Variance Reduction: Understanding the True Impact of Baselines on Policy Optimization
Wesley Chung, Valentin Thomas, Marlos C. Machado and Nicolas Le Roux

2021-06

On the Convergence of Stochastic Extragradient for Bilinear Games with Restarted Iteration Averaging.
Chris Junchi Li, Yaodong Yu, Nicolas Loizou, Gauthier Gidel, Yi Ma, Nicolas Le Roux and Michael I. Jordan
arXiv preprint arXiv:2107.00464
(2021-06-30)
ui.adsabs.harvard.eduPDF

2021-05

Batch Reinforcement Learning Through Continuation Method
Yijie Guo, Shengyu Feng, Nicolas Le Roux, Ed Chi, Honglak Lee and Minmin Chen
ICLR 2021
(2021-05-03)
dblp.uni-trier.dePDF

2021-02

Bridging the Gap Between Adversarial Robustness and Optimization Bias
Fartash Faghri, Cristina Vasconcelos, David J. Fleet, Fabian Pedregosa and Nicolas Le Roux
arXiv preprint arXiv:2102.08868
(2021-02-17)
ui.adsabs.harvard.eduPDF

2021-01

Impact of Aliasing on Generalization in Deep Convolutional Networks
Cristina Vasconcelos, Hugo Larochelle, Vincent Dumoulin, Rob Romijnders, Nicolas Le Roux and Ross Goroshin

2020-11

An Effective Anti-Aliasing Approach for Residual Networks.
Cristina Vasconcelos, Hugo Larochelle, Vincent Dumoulin, Nicolas Le Roux and Ross Goroshin
arXiv preprint arXiv:2011.10675
(2020-11-20)
ui.adsabs.harvard.eduPDF

2020-06

To Each Optimizer a Norm, To Each Norm its Generalization.
Sharan Vaswani, Reza Babanezhad, Jose Gallego, Aaron Mishkin, Simon Lacoste-Julien and Nicolas Le Roux
arXiv preprint arXiv:2006.06821
(2020-06-11)
ui.adsabs.harvard.eduPDF
On the interplay between noise and curvature and its effect on optimization and generalization
Valentin Thomas, Fabian Pedregosa, Bart van Merriënboer, Pierre-Antoine Manzagol, Yoshua Bengio and Nicolas Le Roux
AISTATS 2020
(2020-06-03)
proceedings.mlr.pressPDF

2020-02

The Geometry of Sign Gradient Descent
Lukas Balles, Fabian Pedregosa and Nicolas Le Roux
arXiv preprint arXiv:2002.08056
(2020-02-19)
ui.adsabs.harvard.eduPDF

2020-01

An operator view of policy gradient methods.
Dibya Ghosh, Marlos C. Machado and Nicolas Le Roux

2019-06

On the interplay between noise and curvature and its effect on optimization and generalization
Valentin Thomas, Fabian Pedregosa, Bart van Merriënboer, Pierre-Antoine Mangazol, Yoshua Bengio and Nicolas Le Roux
arXiv preprint arXiv:1906.07774
(2019-06-18)
ui.adsabs.harvard.edu
Information matrices and generalization
Valentin Thomas, Fabian Pedregosa, Bart van Merriënboer, Pierre-Antoine Manzagol, Yoshua Bengio and Nicolas Le Roux
(venue unknown)
(2019-06-18)
dblp.uni-trier.dePDF

2019-05

Understanding the impact of entropy on policy optimization
Zafarali Ahmed, Nicolas Le Roux, Mohammad Norouzi and Dale Schuurmans
The Value Function Polytope in Reinforcement Learning
Robert Dadashi, Adrien Ali Taiga, Nicolas Le Roux, Dale Schuurmans and Marc G. Bellemare

2019-04

Distributional reinforcement learning with linear function approximation
Marc G. Bellemare, Nicolas Le Roux, Pablo Samuel Castro and Subhodeep Moitra

2019-03

Improving NILM by Combining Sensor Data and Linear Programming
Nicolas Roux, Baptiste Vrigneau and Olivier Sentieys
SAS 2019
(2019-03-01)
dblp.uni-trier.de

2019-02

Anytime Tail Averaging.
arXiv preprint arXiv:1902.05083
(2019-02-13)
ui.adsabs.harvard.eduPDF
Negative eigenvalues of the Hessian in deep neural networks
Guillaume Alain, Nicolas Le Roux and Pierre-Antoine Manzagol
arXiv preprint arXiv:1902.02366
(2019-02-06)
ui.adsabs.harvard.eduPDF

2019-01

A Geometric Perspective on Optimal Representations for Reinforcement Learning
Marc G. Bellemare, Will Dabney, Robert Dadashi, Adrien Ali Taïga, Pablo Samuel Castro, Nicolas Le Roux, Dale Schuurmans, Tor Lattimore and Clare Lyle
Reducing the variance in online optimization by transporting past gradients
Sébastien M. R. Arnold, Pierre-Antoine Manzagol, Reza Babanezhad, Ioannis Mitliagkas and Nicolas Le Roux

2018-11

Understanding the impact of entropy in policy learning
Zafarali Ahmed, Nicolas Le Roux, Mohammad Norouzi and Dale Schuurmans
(venue unknown)
(2018-11-27)
arxiv.org

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