Gauthier Gidel

Mila > À propos de Mila > Équipe > Gauthier Gidel
Membre Académique Principal
Gauthier Gidel
Professeur adjoint, Université de Montréal
Gauthier Gidel

Publications

2021-04

A single gradient step finds adversarial examples on random two-layers neural networks
Sébastien Bubeck, Yeshwanth Cherapanamjeri, Gauthier Gidel and Rémi Tachet des Combes
arXiv preprint arXiv:2104.03863
(2021-04-08)
arxiv.orgPDF

2021-03

A Limited-Capacity Minimax Theorem for Non-Convex Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets.
Gauthier Gidel, David Balduzzi, Wojciech Marian Czarnecki, Marta Garnelo and Yoram Bachrach
arXiv: Machine Learning
(2021-03-16)
arxiv.orgPDF
Online Adversarial Attacks.
Andjela Mladenovic, Avishek Joey Bose, Hugo Berard, William L. Hamilton, Simon Lacoste-Julien, Pascal Vincent and Gauthier Gidel
arXiv preprint arXiv:2103.02014
(2021-03-02)
dblp.uni-trier.dePDF

2020-07

Linear Lower Bounds and Conditioning of Differentiable Games
Adam Ibrahim, Waïss Azizian, Gauthier Gidel and Ioannis Mitliagkas
Adversarial Example Games.
Avishek Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien and William L. Hamilton
arXiv preprint arXiv:2007.00720
(2020-07-01)
ui.adsabs.harvard.eduPDF

2020-04

A Closer Look at the Optimization Landscapes of Generative Adversarial Networks
Hugo Berard, Gauthier Gidel, Amjad Almahairi, Pascal Vincent and Simon Lacoste-Julien

2020-01

Adversarial Example Games
Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien and Will Hamilton
NEURIPS 2020
(2020-01-01)
papers.nips.ccPDF
A Tight and Unified Analysis of Gradient-Based Methods for a Whole Spectrum of Differentiable Games.
AISTATS 2020
(2020-01-01)
proceedings.mlr.press
Accelerating Smooth Games by Manipulating Spectral Shapes.
Waïss Azizian, Damien Scieur, Ioannis Mitliagkas, Simon Lacoste-Julien and Gauthier Gidel

2019-06

Lower Bounds and Conditioning of Differentiable Games.
Adam Ibrahim, Waïss Azizian, Gauthier Gidel and Ioannis Mitliagkas
arXiv preprint arXiv:1906.07300
(2019-06-17)
dblp.uni-trier.dePDF
A Tight and Unified Analysis of Gradient-Based Methods for a Whole Spectrum of Games
arXiv preprint arXiv:1906.05945
(2019-06-13)
ui.adsabs.harvard.eduPDF
A Tight and Unified Analysis of Extragradient for a Whole Spectrum of Differentiable Games.
arXiv: Learning
(2019-06-13)
dblp.uni-trier.dePDF

2019-05

Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates
Sharan Vaswani, Aaron Mishkin, Issam H. Laradji, Mark Schmidt, Gauthier Gidel and Simon Lacoste-Julien

2019-04

Negative Momentum for Improved Game Dynamics
Gauthier Gidel, Reyhane Askari Hemmat, Mohammad Pezeshki, Gabriel Huang, Rémi Le Priol, Simon Lacoste-Julien and Ioannis Mitliagkas
AISTATS 2019
(2019-04-11)
proceedings.mlr.pressPDF

2019-01

Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks
Reducing Noise in GAN Training with Variance Reduced Extragradient
Tatjana Chavdarova, Gauthier Gidel, François Fleuret and Simon Lacoste-Julien
Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics
Giancarlo Kerg, Kyle Goyette, Maximilian Puelma Touzel, Gauthier Gidel, Eugene Vorontsov, Yoshua Bengio and Guillaume Lajoie

2018-07

Negative Momentum for Improved Game Dynamics
Gauthier Gidel, Reyhane Askari Hemmat, Mohammad Pezeshki, Remi Lepriol, Gabriel Huang, Simon Lacoste-Julien and Ioannis Mitliagkas
arXiv preprint arXiv:1807.04740
(2018-07-12)
ui.adsabs.harvard.eduPDF

2018-03

Frank-Wolfe Splitting via Augmented Lagrangian Method
Gauthier Gidel, Fabian Pedregosa and Simon Lacoste-Julien

2018-02

A Variational Inequality Perspective on Generative Adversarial Networks
Gauthier Gidel, Hugo Berard, Gaëtan Vignoud, Pascal Vincent and Simon Lacoste-Julien
Parametric Adversarial Divergences are Good Task Losses for Generative Modeling
Gabriel Huang, Hugo Berard, Ahmed Touati, Gauthier Gidel, Pascal Vincent and Simon Lacoste-Julien
ICLR 2018
(2018-02-01)
ui.adsabs.harvard.eduPDF

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