Mila > Team > Gauthier Gidel

Gauthier Gidel

Core Academic Member
Assistant Professor, Université de Montréal, Canada CIFAR AI Chair

I am an assistant professor at Université de Montréal (UdeM) at DIRO and a core faculty member of Mila. I have been a Borealis AI graduate fellow. I am currently a Canada CIFAR AI chair recipient. I have worked at DeepMind and Element AI and have recently been a long-term visitor at the Simons Institute at UC Berkeley. My research interest lies at the intersection between game theory, optimization, and machine learning.

Publications

2021-12

Stochastic Gradient Descent-Ascent and Consensus Optimization for Smooth Games: Convergence Analysis under Expected Co-coercivity
Nicolas Loizou, Hugo Berard, Gauthier Gidel, Ioannis Mitliagkas and Simon Lacoste-Julien
A single gradient step finds adversarial examples on random two-layers neural networks
Sebastien Bubeck, Yeshwanth Cherapanamjeri, Gauthier Gidel and Remi Tachet des Combes

2021-11

Stochastic Extragradient: General Analysis and Improved Rates
Eduard Gorbunov, Hugo Berard, Gauthier Gidel and Nicolas Loizou
arXiv preprint arXiv:2111.08611
(2021-11-16)
dblp.uni-trier.dePDF
Generating Diverse Realistic Laughter for Interactive Art.
M. Mehdi Afsar, Eric Park, Étienne Paquette, Gauthier Gidel, Kory Wallace Mathewson and Eilif Muller
arXiv preprint arXiv:2111.03146
(2021-11-04)
dblp.uni-trier.dePDF

2021-10

Convergence Analysis and Implicit Regularization of Feedback Alignment for Deep Linear Networks.
Manuela Girotti, Ioannis Mitliagkas and Gauthier Gidel
arXiv preprint arXiv:2110.10815
(2021-10-20)
ui.adsabs.harvard.eduPDF
Extragradient Method: O(1/K) Last-Iterate Convergence for Monotone Variational Inequalities and Connections With Cocoercivity.
Eduard Gorbunov, Nicolas Loizou and Gauthier Gidel
arXiv preprint arXiv:2110.04261
(2021-10-08)
ui.adsabs.harvard.eduPDF

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

2021-03

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 Czarnecki, Marta Garnelo and Yoram Bachrach
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)
ui.adsabs.harvard.eduPDF

2021-01

Pick Your Battles: Interaction Graphs as Population-Level Objectives for Strategic Diversity.
Marta Garnelo, Wojciech Marian Czarnecki, Siqi Liu, Dhruva Tirumala, Junhyuk Oh, Gauthier Gidel, Hado van Hasselt and David Balduzzi
Autonomous Agents and Multi-Agent Systems
(2021-01-01)
dl.acm.org[LATEST on arXiv preprint arXiv:2110.04041 (2021-10-08)]

2020-12

Multi-player games in the era of machine learning
(venue unknown)
(2020-12-16)
papyrus.bib.umontreal.ca

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

2020-06

A Tight and Unified Analysis of Gradient-Based Methods for a Whole Spectrum of Differentiable Games.
AISTATS 2020
(2020-06-03)
proceedings.mlr.pressPDF
Accelerating Smooth Games by Manipulating Spectral Shapes.
Waïss Azizian, Damien Scieur, Ioannis Mitliagkas, Simon Lacoste-Julien and Gauthier Gidel

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

2019-06

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