Gauthier Gidel

According to our database, Gauthier Gidel authored at least 72 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Soft Prompt Threats: Attacking Safety Alignment and Unlearning in Open-Source LLMs through the Embedding Space.

Leo Schwinn, David Dobre, Sophie Xhonneux, Gauthier Gidel, Stephan Günnemann

CoRR, 2024

Iterated Denoising Energy Matching for Sampling from Boltzmann Densities.

Tara Akhound-Sadegh, Jarrid Rector-Brooks, Avishek Joey Bose, Sarthak Mittal, Pablo Lemos, Cheng-Hao Liu, Marcin Sendera, Siamak Ravanbakhsh, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Alexander Tong

CoRR, 2024

In-Context Learning Can Re-learn Forbidden Tasks.

Sophie Xhonneux, David Dobre, Jian Tang, Gauthier Gidel, Dhanya Sridhar

CoRR, 2024

2023

Q-learners Can Provably Collude in the Iterated Prisoner's Dilemma.

Quentin Bertrand, Juan Duque, Emilio Calvano, Gauthier Gidel

CoRR, 2023

Adversarial Attacks and Defenses in Large Language Models: Old and New Threats.

Leo Schwinn, David Dobre, Stephan Günnemann, Gauthier Gidel

CoRR, 2023

Proving Linear Mode Connectivity of Neural Networks via Optimal Transport.

Damien Ferbach, Baptiste Goujaud, Gauthier Gidel, Aymeric Dieuleveut

CoRR, 2023

A Persuasive Approach to Combating Misinformation.

Safwan Hossain, Andjela Mladenovic, Yiling Chen, Gauthier Gidel

CoRR, 2023

Expected flow networks in stochastic environments and two-player zero-sum games.

Marco Jiralerspong, Bilun Sun, Danilo Vucetic, Tianyu Zhang, Yoshua Bengio, Gauthier Gidel, Nikolay Malkin

CoRR, 2023

High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise.

Eduard Gorbunov, Abdurakhmon Sadiev, Marina Danilova, Samuel Horváth, Gauthier Gidel, Pavel E. Dvurechensky, Alexander V. Gasnikov, Peter Richtárik

CoRR, 2023

On the Stability of Iterative Retraining of Generative Models on their own Data.

Quentin Bertrand, Avishek Joey Bose, Alexandre Duplessis, Marco Jiralerspong, Gauthier Gidel

CoRR, 2023

AI4GCC - Track 3: Consumption and the Challenges of Multi-Agent RL.

Marco Jiralerspong, Gauthier Gidel

CoRR, 2023

Omega: Optimistic EMA Gradients.

Juan Ramirez, Rohan Sukumaran, Quentin Bertrand, Gauthier Gidel

CoRR, 2023

Synaptic Weight Distributions Depend on the Geometry of Plasticity.

Roman Pogodin, Jonathan Cornford, Arna Ghosh, Gauthier Gidel, Guillaume Lajoie, Blake A. Richards

CoRR, 2023

Raising the Bar for Certified Adversarial Robustness with Diffusion Models.

Thomas Altstidl, David Dobre, Björn M. Eskofier, Gauthier Gidel, Leo Schwinn

CoRR, 2023

Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features.

Aleksandr Beznosikov, David Dobre, Gauthier Gidel

CoRR, 2023

Feature Likelihood Score: Evaluating Generalization of Generative Models Using Samples.

Marco Jiralerspong, Avishek Joey Bose, Gauthier Gidel

CoRR, 2023

Optimal Extragradient-Based Algorithms for Stochastic Variational Inequalities with Separable Structure.

Angela Yuan, Chris Junchi Li, Gauthier Gidel, Michael I. Jordan, Quanquan Gu, Simon S. Du

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Feature Likelihood Score: Evaluating the Generalization of Generative Models Using Samples.

Marco Jiralerspong, Avishek Joey Bose, Ian Gemp, Chongli Qin, Yoram Bachrach, Gauthier Gidel

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

High-Probability Bounds for Stochastic Optimization and Variational Inequalities: the Case of Unbounded Variance.

Abdurakhmon Sadiev, Marina Danilova, Eduard Gorbunov, Samuel Horváth, Gauthier Gidel, Pavel E. Dvurechensky, Alexander V. Gasnikov, Peter Richtárik

Proceedings of the International Conference on Machine Learning, 2023

Nesterov Meets Optimism: Rate-Optimal Separable Minimax Optimization.

Chris Junchi Li, Huizhuo Yuan, Gauthier Gidel, Quanquan Gu, Michael I. Jordan

Proceedings of the International Conference on Machine Learning, 2023

Convergence of Proximal Point and Extragradient-Based Methods Beyond Monotonicity: the Case of Negative Comonotonicity.

Eduard Gorbunov, Adrien B. Taylor, Samuel Horváth, Gauthier Gidel

Proceedings of the International Conference on Machine Learning, 2023

Variance Reduction is an Antidote to Byzantines: Better Rates, Weaker Assumptions and Communication Compression as a Cherry on the Top.

Eduard Gorbunov, Samuel Horváth, Peter Richtárik, Gauthier Gidel

Proceedings of the Eleventh International Conference on Learning Representations, 2023

A General Framework For Proving The Equivariant Strong Lottery Ticket Hypothesis.

Damien Ferbach, Christos Tsirigotis, Gauthier Gidel, Avishek Joey Bose

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Performative Prediction with Neural Networks.

Mehrnaz Mofakhami, Ioannis Mitliagkas, Gauthier Gidel

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

On the Limitations of the Elo, Real-World Games are Transitive, not Additive.

Quentin Bertrand, Wojciech Marian Czarnecki, Gauthier Gidel

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Extragradient with Positive Momentum is Optimal for Games with Cross-Shaped Jacobian Spectrum.

Junhyung Lyle Kim, Gauthier Gidel, Anastasios Kyrillidis, Fabian Pedregosa

CoRR, 2022

Nesterov Meets Optimism: Rate-Optimal Optimistic-Gradient-Based Method for Stochastic Bilinearly-Coupled Minimax Optimization.

Chris Junchi Li, Angela Yuan, Gauthier Gidel, Michael I. Jordan

CoRR, 2022

Dissecting adaptive methods in GANs.

Samy Jelassi, David Dobre, Arthur Mensch, Yuanzhi Li, Gauthier Gidel

CoRR, 2022

Proceedings of the ICML 2022 Expressive Vocalizations Workshop and Competition: Recognizing, Generating, and Personalizing Vocal Bursts.

Alice Baird, Panagiotis Tzirakis, Gauthier Gidel, Marco Jiralerspong, Eilif B. Muller, Kory W. Mathewson, Björn W. Schuller, Erik Cambria, Dacher Keltner, Alan Cowen

CoRR, 2022

Generating Diverse Vocal Bursts with StyleGAN2 and MEL-Spectrograms.

Marco Jiralerspong, Gauthier Gidel

CoRR, 2022

Optimal Extragradient-Based Bilinearly-Coupled Saddle-Point Optimization.

Simon S. Du, Gauthier Gidel, Michael I. Jordan, Chris Junchi Li

CoRR, 2022

The ICML 2022 Expressive Vocalizations Workshop and Competition: Recognizing, Generating, and Personalizing Vocal Bursts.

Alice Baird, Panagiotis Tzirakis, Gauthier Gidel, Marco Jiralerspong, Eilif B. Muller, Kory W. Mathewson, Björn W. Schuller, Erik Cambria, Dacher Keltner, Alan Cowen

CoRR, 2022

The Curse of Unrolling: Rate of Differentiating Through Optimization.

Damien Scieur, Gauthier Gidel, Quentin Bertrand, Fabian Pedregosa

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Last-Iterate Convergence of Optimistic Gradient Method for Monotone Variational Inequalities.

Eduard Gorbunov, Adrien B. Taylor, Gauthier Gidel

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Clipped Stochastic Methods for Variational Inequalities with Heavy-Tailed Noise.

Eduard Gorbunov, Marina Danilova, David Dobre, Pavel E. Dvurechenskii, Alexander V. Gasnikov, Gauthier Gidel

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Beyond L1: Faster and Better Sparse Models with skglm.

Quentin Bertrand, Quentin Klopfenstein, Pierre-Antoine Bannier, Gauthier Gidel, Mathurin Massias

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Only tails matter: Average-Case Universality and Robustness in the Convex Regime.

Leonardo Cunha, Gauthier Gidel, Fabian Pedregosa, Damien Scieur, Courtney Paquette

Proceedings of the International Conference on Machine Learning, 2022

Generalized Natural Gradient Flows in Hidden Convex-Concave Games and GANs.

Andjela Mladenovic, Iosif Sakos, Gauthier Gidel, Georgios Piliouras

Proceedings of the Tenth International Conference on Learning Representations, 2022

Online Adversarial Attacks.

Andjela Mladenovic, Avishek Joey Bose, Hugo Berard, William L. Hamilton, Simon Lacoste-Julien, Pascal Vincent, Gauthier Gidel

Proceedings of the Tenth International Conference on Learning Representations, 2022

On the Convergence of Stochastic Extragradient for Bilinear Games using Restarted Iteration Averaging.

Chris Junchi Li, Yaodong Yu, Nicolas Loizou, Gauthier Gidel, Yi Ma, Nicolas Le Roux, Michael I. Jordan

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Extragradient Method: O(1/K) Last-Iterate Convergence for Monotone Variational Inequalities and Connections With Cocoercivity.

Eduard Gorbunov, Nicolas Loizou, Gauthier Gidel

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Stochastic Extragradient: General Analysis and Improved Rates.

Eduard Gorbunov, Hugo Berard, Gauthier Gidel, Nicolas Loizou

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Generating Diverse Realistic Laughter for Interactive Art.

M. Mehdi Afsar, Eric Park, Étienne Paquette, Gauthier Gidel, Kory W. Mathewson, Eilif B. Muller

CoRR, 2021

Convergence Analysis and Implicit Regularization of Feedback Alignment for Deep Linear Networks.

Manuela Girotti, Ioannis Mitliagkas, Gauthier Gidel

CoRR, 2021

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, Michael I. Jordan

CoRR, 2021

Stochastic Gradient Descent-Ascent and Consensus Optimization for Smooth Games: Convergence Analysis under Expected Co-coercivity.

Nicolas Loizou, Hugo Berard, Gauthier Gidel, Ioannis Mitliagkas, Simon Lacoste-Julien

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

A single gradient step finds adversarial examples on random two-layers neural networks.

Sébastien Bubeck, Yeshwanth Cherapanamjeri, Gauthier Gidel, Remi Tachet des Combes

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

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, David Balduzzi

Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

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, Yoram Bachrach

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Minimax Theorem for Latent Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets.

Gauthier Gidel, David Balduzzi, Wojciech Marian Czarnecki, Marta Garnelo, Yoram Bachrach

CoRR, 2020

Real World Games Look Like Spinning Tops.

Wojciech M. Czarnecki, Gauthier Gidel, Brendan D. Tracey, Karl Tuyls, Shayegan Omidshafiei, David Balduzzi, Max Jaderberg

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Adversarial Example Games.

Avishek Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien, William L. Hamilton

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Linear Lower Bounds and Conditioning of Differentiable Games.

Adam Ibrahim, Waïss Azizian, Gauthier Gidel, Ioannis Mitliagkas

Proceedings of the 37th International Conference on Machine Learning, 2020

A Closer Look at the Optimization Landscapes of Generative Adversarial Networks.

Hugo Berard, Gauthier Gidel, Amjad Almahairi, Pascal Vincent, Simon Lacoste-Julien

Proceedings of the 8th International Conference on Learning Representations, 2020

Finite Regret and Cycles with Fixed Step-Size via Alternating Gradient Descent-Ascent.

James P. Bailey, Gauthier Gidel, Georgios Piliouras

Proceedings of the Conference on Learning Theory, 2020

Accelerating Smooth Games by Manipulating Spectral Shapes.

Waïss Azizian, Damien Scieur, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

A Tight and Unified Analysis of Gradient-Based Methods for a Whole Spectrum of Differentiable Games.

Waïss Azizian, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Lower Bounds and Conditioning of Differentiable Games.

Adam Ibrahim, Waïss Azizian, Gauthier Gidel, Ioannis Mitliagkas

CoRR, 2019

A Tight and Unified Analysis of Extragradient for a Whole Spectrum of Differentiable Games.

Waïss Azizian, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel

CoRR, 2019

Implicit Regularization of Discrete Gradient Dynamics in Deep Linear Neural Networks.

Gauthier Gidel, Francis R. Bach, Simon Lacoste-Julien

CoRR, 2019

Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates.

Sharan Vaswani, Aaron Mishkin, Issam H. Laradji, Mark Schmidt, Gauthier Gidel, Simon Lacoste-Julien

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

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, Guillaume Lajoie

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks.

Gauthier Gidel, Francis R. Bach, Simon Lacoste-Julien

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Reducing Noise in GAN Training with Variance Reduced Extragradient.

Tatjana Chavdarova, Gauthier Gidel, François Fleuret, Simon Lacoste-Julien

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Variational Inequality Perspective on Generative Adversarial Networks.

Gauthier Gidel, Hugo Berard, Gaëtan Vignoud, Pascal Vincent, Simon Lacoste-Julien

Proceedings of the 7th International Conference on Learning Representations, 2019

Negative Momentum for Improved Game Dynamics.

Gauthier Gidel, Reyhane Askari Hemmat, Mohammad Pezeshki, Rémi Le Priol, Gabriel Huang, Simon Lacoste-Julien, Ioannis Mitliagkas

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

A Variational Inequality Perspective on Generative Adversarial Nets.

Gauthier Gidel, Hugo Berard, Pascal Vincent, Simon Lacoste-Julien

CoRR, 2018

Adaptive Three Operator Splitting.

Fabian Pedregosa, Gauthier Gidel

Proceedings of the 35th International Conference on Machine Learning, 2018

Parametric Adversarial Divergences are Good Task Losses for Generative Modeling.

Gabriel Huang, Hugo Berard, Ahmed Touati, Gauthier Gidel, Pascal Vincent, Simon Lacoste-Julien

Proceedings of the 6th International Conference on Learning Representations, 2018

Frank-Wolfe Splitting via Augmented Lagrangian Method.

Gauthier Gidel, Fabian Pedregosa, Simon Lacoste-Julien

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Adversarial Divergences are Good Task Losses for Generative Modeling.

Gabriel Huang, Gauthier Gidel, Hugo Berard, Ahmed Touati, Simon Lacoste-Julien

CoRR, 2017

Frank-Wolfe Algorithms for Saddle Point Problems.

Gauthier Gidel, Tony Jebara, Simon Lacoste-Julien

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017