Gauthier Gidel

134 papers A* 41A 16Journal 74Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Coin Flip for Safety: LLM Judges Fail to Reliably Measure Adversarial Robustness. CoRR Leo Schwinn, Moritz Ladenburger, Tim Beyer, Mehrnaz Mofakhami, Gauthier Gidel, Stephan Günnemann
2026	J	`jnl`	Logarithmic-time Schedules for Scaling Language Models with Momentum. CoRR Damien Ferbach, Courtney Paquette, Gauthier Gidel, Katie Everett, Elliot Paquette
2025	J	`jnl`	A generative approach to LLM harmfulness detection with special red flag tokens. CoRR Sophie Xhonneux, David Dobre, Mehrnaz Mohfakhami, Leo Schwinn, Gauthier Gidel
2025	A*	`conf`	Advantage Alignment Algorithms. ICLR Juan Agustin Duque, Milad Aghajohari, Tim Cooijmans, Razvan Ciuca, Tianyu Zhang, Gauthier Gidel, Aaron C. Courville
2025	J	`jnl`	Adversarial Alignment for LLMs Requires Simpler, Reproducible, and More Measurable Objectives. CoRR Leo Schwinn, Yan Scholten, Tom Wollschläger, Sophie Xhonneux, Stephen Casper, Stephan Günnemann, Gauthier Gidel
2025	J	`jnl`	Dimension-adapted Momentum Outscales SGD. CoRR Damien Ferbach, Katie Everett, Gauthier Gidel, Elliot Paquette, Courtney Paquette
2025	J	`jnl`	LLM-Safety Evaluations Lack Robustness. CoRR Tim Beyer, Sophie Xhonneux, Simon Geisler, Gauthier Gidel, Leo Schwinn, Stephan Günnemann
2025	A*	`conf`	Learning Diverse Attacks on Large Language Models for Robust Red-Teaming and Safety Tuning. ICLR Seanie Lee, Minsu Kim, Lynn Cherif, David Dobre, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Moksh Jain
2025	A	`conf`	Performative Prediction on Games and Mechanism Design. AISTATS António Góis, Mehrnaz Mofakhami, Fernando P. Santos, Gauthier Gidel, Simon Lacoste-Julien
2025	J	`jnl`	Robust Reinforcement Learning for Discrete Compositional Generation via General Soft Operators. CoRR Marco Jiralerspong, Esther Derman, Danilo Vucetic, Nikolay Malkin, Bilun Sun, Tianyu Zhang, Pierre-Luc Bacon, Gauthier Gidel
2025	A*	`conf`	Self-Play Q-Learners Can Provably Collude in the Iterated Prisoner's Dilemma. ICML Quentin Bertrand, Juan Agustin Duque, Emilio Calvano, Gauthier Gidel
2025	A*	`conf`	Solving hidden monotone variational inequalities with surrogate losses. ICLR Ryan D'Orazio, Danilo Vucetic, Zichu Liu, Junhyung Lyle Kim, Ioannis Mitliagkas, Gauthier Gidel
2024	A*	`conf`	A Persuasive Approach to Combating Misinformation. ICML Safwan Hossain, Andjela Mladenovic, Yiling Chen, Gauthier Gidel
2024	A*	`conf`	Efficient Adversarial Training in LLMs with Continuous Attacks. NeurIPS Sophie Xhonneux, Alessandro Sordoni, Stephan Günnemann, Gauthier Gidel, Leo Schwinn
2024	J	`jnl`	Efficient Adversarial Training in LLMs with Continuous Attacks. CoRR Sophie Xhonneux, Alessandro Sordoni, Stephan Günnemann, Gauthier Gidel, Leo Schwinn
2024	A*	`conf`	Expected flow networks in stochastic environments and two-player zero-sum games. ICLR Marco Jiralerspong, Bilun Sun, Danilo Vucetic, Tianyu Zhang, Yoshua Bengio, Gauthier Gidel, Nikolay Malkin
2024	J	`jnl`	General Causal Imputation via Synthetic Interventions. CoRR Marco Jiralerspong, Thomas Jiralerspong, Vedant Shah, Dhanya Sridhar, Gauthier Gidel
2024	A*	`conf`	High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise. ICML Eduard Gorbunov, Abdurakhmon Sadiev, Marina Danilova, Samuel Horváth, Gauthier Gidel, Pavel E. Dvurechensky, Alexander V. Gasnikov, Peter Richtárik
2024	J	`jnl`	In-Context Learning Can Re-learn Forbidden Tasks. CoRR Sophie Xhonneux, David Dobre, Jian Tang, Gauthier Gidel, Dhanya Sridhar
2024	J	`jnl`	Investigating the Benefits of Nonlinear Action Maps in Data-Driven Teleoperation. CoRR Michael Przystupa, Gauthier Gidel, Matthew E. Taylor, Martin Jägersand, Justus H. Piater, Samuele Tosatto
2024	A*	`conf`	Iterated Denoising Energy Matching for Sampling from Boltzmann Densities. ICML 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
2024	J	`jnl`	Iterated Denoising Energy Matching for Sampling from Boltzmann Densities. CoRR 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
2024	J	`jnl`	Learning diverse attacks on large language models for robust red-teaming and safety tuning. CoRR Seanie Lee, Minsu Kim, Lynn Cherif, David Dobre, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Moksh Jain
2024	A	`conf`	Local Linearity is All You Need (in Data-Driven Teleoperation). IROS Michael Przystupa, Gauthier Gidel, Matthew E. Taylor, Martin Jägersand, Justus H. Piater, Samuele Tosatto
2024	A*	`conf`	On the Scalability of Certified Adversarial Robustness with Generated Data. NeurIPS Thomas Altstidl, David Dobre, Arthur Kosmala, Bjoern M. Eskofier, Gauthier Gidel, Leo Schwinn
2024	A*	`conf`	On the Stability of Iterative Retraining of Generative Models on their own Data. ICLR Quentin Bertrand, Avishek Joey Bose, Alexandre Duplessis, Marco Jiralerspong, Gauthier Gidel
2024	J	`jnl`	Performative Prediction on Games and Mechanism Design. CoRR António Góis, Mehrnaz Mofakhami, Fernando P. Santos, Simon Lacoste-Julien, Gauthier Gidel
2024	A	`conf`	Proving Linear Mode Connectivity of Neural Networks via Optimal Transport. AISTATS Damien Ferbach, Baptiste Goujaud, Gauthier Gidel, Aymeric Dieuleveut
2024	A*	`conf`	Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features. ICML Aleksandr Beznosikov, David Dobre, Gauthier Gidel
2024	A*	`conf`	Self-Consuming Generative Models with Curated Data Provably Optimize Human Preferences. NeurIPS Damien Ferbach, Quentin Bertrand, Avishek Joey Bose, Gauthier Gidel
2024	J	`jnl`	Self-Consuming Generative Models with Curated Data Provably Optimize Human Preferences. CoRR Damien Ferbach, Quentin Bertrand, Avishek Joey Bose, Gauthier Gidel
2024	A*	`conf`	Soft Prompt Threats: Attacking Safety Alignment and Unlearning in Open-Source LLMs through the Embedding Space. NeurIPS Leo Schwinn, David Dobre, Sophie Xhonneux, Gauthier Gidel, Stephan Günnemann
2024	J	`jnl`	Soft Prompt Threats: Attacking Safety Alignment and Unlearning in Open-Source LLMs through the Embedding Space. CoRR Leo Schwinn, David Dobre, Sophie Xhonneux, Gauthier Gidel, Stephan Günnemann
2024	J	`jnl`	Solving Hidden Monotone Variational Inequalities with Surrogate Losses. CoRR Ryan D'Orazio, Danilo Vucetic, Zichu Liu, Junhyung Lyle Kim, Ioannis Mitliagkas, Gauthier Gidel
2024	A	`conf`	Stochastic Frank-Wolfe: Unified Analysis and Zoo of Special Cases. AISTATS Ruslan Nazykov, Aleksandr Shestakov, Vladimir Solodkin, Aleksandr Beznosikov, Gauthier Gidel, Alexander V. Gasnikov
2024	A*	`conf`	Synaptic Weight Distributions Depend on the Geometry of Plasticity. ICLR Roman Pogodin, Jonathan Cornford, Arna Ghosh, Gauthier Gidel, Guillaume Lajoie, Blake Aaron Richards
2024	J	`jnl`	Tight Lower Bounds and Improved Convergence in Performative Prediction. CoRR Pedram Khorsandi, Rushil Gupta, Mehrnaz Mofakhami, Simon Lacoste-Julien, Gauthier Gidel
2024	J	`jnl`	When is Momentum Extragradient Optimal? A Polynomial-Based Analysis. Trans. Mach. Learn. Res. Junhyung Lyle Kim, Gauthier Gidel, Anastasios Kyrillidis, Fabian Pedregosa
2023	A*	`conf`	A General Framework For Proving The Equivariant Strong Lottery Ticket Hypothesis. ICLR Damien Ferbach, Christos Tsirigotis, Gauthier Gidel, Avishek Joey Bose
2023	J	`jnl`	A Persuasive Approach to Combating Misinformation. CoRR Safwan Hossain, Andjela Mladenovic, Yiling Chen, Gauthier Gidel
2023	J	`jnl`	AI4GCC - Track 3: Consumption and the Challenges of Multi-Agent RL. CoRR Marco Jiralerspong, Gauthier Gidel
2023	—	`conf`	Adversarial Attacks and Defenses in Large Language Models: Old and New Threats. ICBINB Leo Schwinn, David Dobre, Stephan Günnemann, Gauthier Gidel
2023	J	`jnl`	Adversarial Attacks and Defenses in Large Language Models: Old and New Threats. CoRR Leo Schwinn, David Dobre, Stephan Günnemann, Gauthier Gidel
2023	A*	`conf`	Convergence of Proximal Point and Extragradient-Based Methods Beyond Monotonicity: the Case of Negative Comonotonicity. ICML Eduard Gorbunov, Adrien B. Taylor, Samuel Horváth, Gauthier Gidel
2023	J	`jnl`	Expected flow networks in stochastic environments and two-player zero-sum games. CoRR Marco Jiralerspong, Bilun Sun, Danilo Vucetic, Tianyu Zhang, Yoshua Bengio, Gauthier Gidel, Nikolay Malkin
2023	J	`jnl`	Feature Likelihood Score: Evaluating Generalization of Generative Models Using Samples. CoRR Marco Jiralerspong, Avishek Joey Bose, Gauthier Gidel
2023	A*	`conf`	Feature Likelihood Score: Evaluating the Generalization of Generative Models Using Samples. NeurIPS Marco Jiralerspong, Avishek Joey Bose, Ian Gemp, Chongli Qin, Yoram Bachrach, Gauthier Gidel
2023	A*	`conf`	High-Probability Bounds for Stochastic Optimization and Variational Inequalities: the Case of Unbounded Variance. ICML Abdurakhmon Sadiev, Marina Danilova, Eduard Gorbunov, Samuel Horváth, Gauthier Gidel, Pavel E. Dvurechensky, Alexander V. Gasnikov, Peter Richtárik
2023	J	`jnl`	High-Probability Bounds for Stochastic Optimization and Variational Inequalities: the Case of Unbounded Variance. CoRR Abdurakhmon Sadiev, Marina Danilova, Eduard Gorbunov, Samuel Horváth, Gauthier Gidel, Pavel E. Dvurechensky, Alexander V. Gasnikov, Peter Richtárik
2023	J	`jnl`	High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise. CoRR Eduard Gorbunov, Abdurakhmon Sadiev, Marina Danilova, Samuel Horváth, Gauthier Gidel, Pavel E. Dvurechensky, Alexander V. Gasnikov, Peter Richtárik
2023	A*	`conf`	Nesterov Meets Optimism: Rate-Optimal Separable Minimax Optimization. ICML Chris Junchi Li, Huizhuo Yuan, Gauthier Gidel, Quanquan Gu, Michael I. Jordan
2023	J	`jnl`	Omega: Optimistic EMA Gradients. CoRR Juan Ramirez, Rohan Sukumaran, Quentin Bertrand, Gauthier Gidel
2023	A	`conf`	On the Limitations of the Elo, Real-World Games are Transitive, not Additive. AISTATS Quentin Bertrand, Wojciech Marian Czarnecki, Gauthier Gidel
2023	J	`jnl`	On the Stability of Iterative Retraining of Generative Models on their own Data. CoRR Quentin Bertrand, Avishek Joey Bose, Alexandre Duplessis, Marco Jiralerspong, Gauthier Gidel
2023	A*	`conf`	Optimal Extragradient-Based Algorithms for Stochastic Variational Inequalities with Separable Structure. NeurIPS Angela Yuan, Chris Junchi Li, Gauthier Gidel, Michael I. Jordan, Quanquan Gu, Simon S. Du
2023	A	`conf`	Performative Prediction with Neural Networks. AISTATS Mehrnaz Mofakhami, Ioannis Mitliagkas, Gauthier Gidel
2023	J	`jnl`	Performative Prediction with Neural Networks. CoRR Mehrnaz Mofakhami, Ioannis Mitliagkas, Gauthier Gidel
2023	J	`jnl`	Proving Linear Mode Connectivity of Neural Networks via Optimal Transport. CoRR Damien Ferbach, Baptiste Goujaud, Gauthier Gidel, Aymeric Dieuleveut
2023	J	`jnl`	Q-learners Can Provably Collude in the Iterated Prisoner's Dilemma. CoRR Quentin Bertrand, Juan Agustin Duque, Emilio Calvano, Gauthier Gidel
2023	J	`jnl`	Raising the Bar for Certified Adversarial Robustness with Diffusion Models. CoRR Thomas Altstidl, David Dobre, Björn M. Eskofier, Gauthier Gidel, Leo Schwinn
2023	J	`jnl`	Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features. CoRR Aleksandr Beznosikov, David Dobre, Gauthier Gidel
2023	J	`jnl`	Synaptic Weight Distributions Depend on the Geometry of Plasticity. CoRR Roman Pogodin, Jonathan Cornford, Arna Ghosh, Gauthier Gidel, Guillaume Lajoie, Blake A. Richards
2023	A*	`conf`	Variance Reduction is an Antidote to Byzantines: Better Rates, Weaker Assumptions and Communication Compression as a Cherry on the Top. ICLR Eduard Gorbunov, Samuel Horváth, Peter Richtárik, Gauthier Gidel
2022	J	`jnl`	A General Framework For Proving The Equivariant Strong Lottery Ticket Hypothesis. CoRR Damien Ferbach, Christos Tsirigotis, Gauthier Gidel, Avishek Joey Bose
2022	A*	`conf`	Beyond L1: Faster and Better Sparse Models with skglm. NeurIPS Quentin Bertrand, Quentin Klopfenstein, Pierre-Antoine Bannier, Gauthier Gidel, Mathurin Massias
2022	J	`jnl`	Beyond L1: Faster and Better Sparse Models with skglm. CoRR Quentin Bertrand, Quentin Klopfenstein, Pierre-Antoine Bannier, Gauthier Gidel, Mathurin Massias
2022	A*	`conf`	Clipped Stochastic Methods for Variational Inequalities with Heavy-Tailed Noise. NeurIPS Eduard Gorbunov, Marina Danilova, David Dobre, Pavel E. Dvurechenskii, Alexander V. Gasnikov, Gauthier Gidel
2022	J	`jnl`	Clipped Stochastic Methods for Variational Inequalities with Heavy-Tailed Noise. CoRR Eduard Gorbunov, Marina Danilova, David Dobre, Pavel E. Dvurechensky, Alexander V. Gasnikov, Gauthier Gidel
2022	J	`jnl`	Dissecting adaptive methods in GANs. CoRR Samy Jelassi, David Dobre, Arthur Mensch, Yuanzhi Li, Gauthier Gidel
2022	A	`conf`	Extragradient Method: O(1/K) Last-Iterate Convergence for Monotone Variational Inequalities and Connections With Cocoercivity. AISTATS Eduard Gorbunov, Nicolas Loizou, Gauthier Gidel
2022	J	`jnl`	Extragradient with Positive Momentum is Optimal for Games with Cross-Shaped Jacobian Spectrum. CoRR Junhyung Lyle Kim, Gauthier Gidel, Anastasios Kyrillidis, Fabian Pedregosa
2022	A*	`conf`	Generalized Natural Gradient Flows in Hidden Convex-Concave Games and GANs. ICLR Andjela Mladenovic, Iosif Sakos, Gauthier Gidel, Georgios Piliouras
2022	J	`jnl`	Generating Diverse Vocal Bursts with StyleGAN2 and MEL-Spectrograms. CoRR Marco Jiralerspong, Gauthier Gidel
2022	A*	`conf`	Last-Iterate Convergence of Optimistic Gradient Method for Monotone Variational Inequalities. NeurIPS Eduard Gorbunov, Adrien B. Taylor, Gauthier Gidel
2022	J	`jnl`	Nesterov Meets Optimism: Rate-Optimal Optimistic-Gradient-Based Method for Stochastic Bilinearly-Coupled Minimax Optimization. CoRR Chris Junchi Li, Angela Yuan, Gauthier Gidel, Michael I. Jordan
2022	A	`conf`	On the Convergence of Stochastic Extragradient for Bilinear Games using Restarted Iteration Averaging. AISTATS Chris Junchi Li, Yaodong Yu, Nicolas Loizou, Gauthier Gidel, Yi Ma, Nicolas Le Roux, Michael I. Jordan
2022	J	`jnl`	On the Limitations of Elo: Real-World Games, are Transitive, not Additive. CoRR Quentin Bertrand, Wojciech Marian Czarnecki, Gauthier Gidel
2022	A*	`conf`	Online Adversarial Attacks. ICLR Andjela Mladenovic, Avishek Joey Bose, Hugo Berard, William L. Hamilton, Simon Lacoste-Julien, Pascal Vincent, Gauthier Gidel
2022	J	`jnl`	Only Tails Matter: Average-Case Universality and Robustness in the Convex Regime. CoRR Leonardo Cunha, Gauthier Gidel, Fabian Pedregosa, Damien Scieur, Courtney Paquette
2022	A*	`conf`	Only tails matter: Average-Case Universality and Robustness in the Convex Regime. ICML Leonardo Cunha, Gauthier Gidel, Fabian Pedregosa, Damien Scieur, Courtney Paquette
2022	J	`jnl`	Optimal Extragradient-Based Bilinearly-Coupled Saddle-Point Optimization. CoRR Simon S. Du, Gauthier Gidel, Michael I. Jordan, Chris Junchi Li
2022	J	`jnl`	Proceedings of the ICML 2022 Expressive Vocalizations Workshop and Competition: Recognizing, Generating, and Personalizing Vocal Bursts. CoRR Alice Baird, Panagiotis Tzirakis, Gauthier Gidel, Marco Jiralerspong, Eilif B. Muller, Kory W. Mathewson, Björn W. Schuller, Erik Cambria, Dacher Keltner, Alan Cowen
2022	A	`conf`	Stochastic Extragradient: General Analysis and Improved Rates. AISTATS Eduard Gorbunov, Hugo Berard, Gauthier Gidel, Nicolas Loizou
2022	A*	`conf`	The Curse of Unrolling: Rate of Differentiating Through Optimization. NeurIPS Damien Scieur, Gauthier Gidel, Quentin Bertrand, Fabian Pedregosa
2022	J	`jnl`	The ICML 2022 Expressive Vocalizations Workshop and Competition: Recognizing, Generating, and Personalizing Vocal Bursts. CoRR Alice Baird, Panagiotis Tzirakis, Gauthier Gidel, Marco Jiralerspong, Eilif B. Muller, Kory W. Mathewson, Björn W. Schuller, Erik Cambria, Dacher Keltner, Alan Cowen
2022	J	`jnl`	Variance Reduction is an Antidote to Byzantines: Better Rates, Weaker Assumptions and Communication Compression as a Cherry on the Top. CoRR Eduard Gorbunov, Samuel Horváth, Peter Richtárik, Gauthier Gidel
2021	A	`conf`	A Limited-Capacity Minimax Theorem for Non-Convex Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets. AISTATS Gauthier Gidel, David Balduzzi, Wojciech Czarnecki, Marta Garnelo, Yoram Bachrach
2021	A*	`conf`	A single gradient step finds adversarial examples on random two-layers neural networks. NeurIPS Sébastien Bubeck, Yeshwanth Cherapanamjeri, Gauthier Gidel, Remi Tachet des Combes
2021	J	`jnl`	A single gradient step finds adversarial examples on random two-layers neural networks. CoRR Sébastien Bubeck, Yeshwanth Cherapanamjeri, Gauthier Gidel, Rémi Tachet des Combes
2021	J	`jnl`	Convergence Analysis and Implicit Regularization of Feedback Alignment for Deep Linear Networks. CoRR Manuela Girotti, Ioannis Mitliagkas, Gauthier Gidel
2021	J	`jnl`	Extragradient Method: O(1/K) Last-Iterate Convergence for Monotone Variational Inequalities and Connections With Cocoercivity. CoRR Eduard Gorbunov, Nicolas Loizou, Gauthier Gidel
2021	J	`jnl`	Generating Diverse Realistic Laughter for Interactive Art. CoRR M. Mehdi Afsar, Eric Park, Étienne Paquette, Gauthier Gidel, Kory W. Mathewson, Eilif B. Muller
2021	J	`jnl`	On the Convergence of Stochastic Extragradient for Bilinear Games with Restarted Iteration Averaging. CoRR Chris Junchi Li, Yaodong Yu, Nicolas Loizou, Gauthier Gidel, Yi Ma, Nicolas Le Roux, Michael I. Jordan
2021	J	`jnl`	Online Adversarial Attacks. CoRR Andjela Mladenovic, Avishek Joey Bose, Hugo Berard, William L. Hamilton, Simon Lacoste-Julien, Pascal Vincent, Gauthier Gidel
2021	A	`conf`	Pick Your Battles: Interaction Graphs as Population-Level Objectives for Strategic Diversity. AAMAS Marta Garnelo, Wojciech Marian Czarnecki, Siqi Liu, Dhruva Tirumala, Junhyuk Oh, Gauthier Gidel, Hado van Hasselt, David Balduzzi
2021	J	`jnl`	Pick Your Battles: Interaction Graphs as Population-Level Objectives for Strategic Diversity. CoRR Marta Garnelo, Wojciech Marian Czarnecki, Siqi Liu, Dhruva Tirumala, Junhyuk Oh, Gauthier Gidel, Hado van Hasselt, David Balduzzi
2021	J	`jnl`	Stochastic Extragradient: General Analysis and Improved Rates. CoRR Eduard Gorbunov, Hugo Berard, Gauthier Gidel, Nicolas Loizou
2021	A*	`conf`	Stochastic Gradient Descent-Ascent and Consensus Optimization for Smooth Games: Convergence Analysis under Expected Co-coercivity. NeurIPS Nicolas Loizou, Hugo Berard, Gauthier Gidel, Ioannis Mitliagkas, Simon Lacoste-Julien
2021	J	`jnl`	Stochastic Gradient Descent-Ascent and Consensus Optimization for Smooth Games: Convergence Analysis under Expected Co-coercivity. CoRR Nicolas Loizou, Hugo Berard, Gauthier Gidel, Ioannis Mitliagkas, Simon Lacoste-Julien
2020	A*	`conf`	A Closer Look at the Optimization Landscapes of Generative Adversarial Networks. ICLR Hugo Berard, Gauthier Gidel, Amjad Almahairi, Pascal Vincent, Simon Lacoste-Julien
2020	A	`conf`	A Tight and Unified Analysis of Gradient-Based Methods for a Whole Spectrum of Differentiable Games. AISTATS Waïss Azizian, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel
2020	A	`conf`	Accelerating Smooth Games by Manipulating Spectral Shapes. AISTATS Waïss Azizian, Damien Scieur, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel
2020	J	`jnl`	Accelerating Smooth Games by Manipulating Spectral Shapes. CoRR Waïss Azizian, Damien Scieur, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel
2020	A*	`conf`	Adversarial Example Games. NeurIPS Avishek Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien, William L. Hamilton
2020	J	`jnl`	Adversarial Example Games. CoRR Avishek Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien, William L. Hamilton
2020	A*	`conf`	Finite Regret and Cycles with Fixed Step-Size via Alternating Gradient Descent-Ascent. COLT James P. Bailey, Gauthier Gidel, Georgios Piliouras
2020	A*	`conf`	Linear Lower Bounds and Conditioning of Differentiable Games. ICML Adam Ibrahim, Waïss Azizian, Gauthier Gidel, Ioannis Mitliagkas
2020	J	`jnl`	Minimax Theorem for Latent Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets. CoRR Gauthier Gidel, David Balduzzi, Wojciech Marian Czarnecki, Marta Garnelo, Yoram Bachrach
2020	A*	`conf`	Real World Games Look Like Spinning Tops. NeurIPS Wojciech M. Czarnecki, Gauthier Gidel, Brendan D. Tracey, Karl Tuyls, Shayegan Omidshafiei, David Balduzzi, Max Jaderberg
2020	J	`jnl`	Real World Games Look Like Spinning Tops. CoRR Wojciech Marian Czarnecki, Gauthier Gidel, Brendan D. Tracey, Karl Tuyls, Shayegan Omidshafiei, David Balduzzi, Max Jaderberg
2019	J	`jnl`	A Closer Look at the Optimization Landscapes of Generative Adversarial Networks. CoRR Hugo Berard, Gauthier Gidel, Amjad Almahairi, Pascal Vincent, Simon Lacoste-Julien
2019	J	`jnl`	A Tight and Unified Analysis of Extragradient for a Whole Spectrum of Differentiable Games. CoRR Waïss Azizian, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel
2019	—	`conf`	A Variational Inequality Perspective on Generative Adversarial Networks. ICLR (Poster) Gauthier Gidel, Hugo Berard, Gaëtan Vignoud, Pascal Vincent, Simon Lacoste-Julien
2019	J	`jnl`	Finite Regret and Cycles with Fixed Step-Size via Alternating Gradient Descent-Ascent. CoRR James P. Bailey, Gauthier Gidel, Georgios Piliouras
2019	J	`jnl`	Implicit Regularization of Discrete Gradient Dynamics in Deep Linear Neural Networks. CoRR Gauthier Gidel, Francis R. Bach, Simon Lacoste-Julien
2019	A*	`conf`	Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks. NeurIPS Gauthier Gidel, Francis R. Bach, Simon Lacoste-Julien
2019	J	`jnl`	Lower Bounds and Conditioning of Differentiable Games. CoRR Adam Ibrahim, Waïss Azizian, Gauthier Gidel, Ioannis Mitliagkas
2019	A	`conf`	Negative Momentum for Improved Game Dynamics. AISTATS Gauthier Gidel, Reyhane Askari Hemmat, Mohammad Pezeshki, Rémi Le Priol, Gabriel Huang, Simon Lacoste-Julien, Ioannis Mitliagkas
2019	A*	`conf`	Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics. NeurIPS Giancarlo Kerg, Kyle Goyette, Maximilian Puelma Touzel, Gauthier Gidel, Eugene Vorontsov, Yoshua Bengio, Guillaume Lajoie
2019	J	`jnl`	Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics. CoRR Giancarlo Kerg, Kyle Goyette, Maximilian Puelma Touzel, Gauthier Gidel, Eugene Vorontsov, Yoshua Bengio, Guillaume Lajoie
2019	A*	`conf`	Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates. NeurIPS Sharan Vaswani, Aaron Mishkin, Issam H. Laradji, Mark Schmidt, Gauthier Gidel, Simon Lacoste-Julien
2019	J	`jnl`	Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates. CoRR Sharan Vaswani, Aaron Mishkin, Issam H. Laradji, Mark Schmidt, Gauthier Gidel, Simon Lacoste-Julien
2019	A*	`conf`	Reducing Noise in GAN Training with Variance Reduced Extragradient. NeurIPS Tatjana Chavdarova, Gauthier Gidel, François Fleuret, Simon Lacoste-Julien
2019	J	`jnl`	Reducing Noise in GAN Training with Variance Reduced Extragradient. CoRR Tatjana Chavdarova, Gauthier Gidel, François Fleuret, Simon Lacoste-Julien
2018	J	`jnl`	A Variational Inequality Perspective on Generative Adversarial Nets. CoRR Gauthier Gidel, Hugo Berard, Pascal Vincent, Simon Lacoste-Julien
2018	A*	`conf`	Adaptive Three Operator Splitting. ICML Fabian Pedregosa, Gauthier Gidel
2018	J	`jnl`	Adaptive Three Operator Splitting. CoRR Fabian Pedregosa, Gauthier Gidel
2018	A	`conf`	Frank-Wolfe Splitting via Augmented Lagrangian Method. AISTATS Gauthier Gidel, Fabian Pedregosa, Simon Lacoste-Julien
2018	J	`jnl`	Frank-Wolfe Splitting via Augmented Lagrangian Method. CoRR Gauthier Gidel, Fabian Pedregosa, Simon Lacoste-Julien
2018	J	`jnl`	Negative Momentum for Improved Game Dynamics. CoRR Gauthier Gidel, Reyhane Askari Hemmat, Mohammad Pezeshki, Gabriel Huang, Rémi Le Priol, Simon Lacoste-Julien, Ioannis Mitliagkas
2018	—	`conf`	Parametric Adversarial Divergences are Good Task Losses for Generative Modeling. ICLR (Workshop) Gabriel Huang, Hugo Berard, Ahmed Touati, Gauthier Gidel, Pascal Vincent, Simon Lacoste-Julien
2017	J	`jnl`	Adversarial Divergences are Good Task Losses for Generative Modeling. CoRR Gabriel Huang, Gauthier Gidel, Hugo Berard, Ahmed Touati, Simon Lacoste-Julien
2017	A	`conf`	Frank-Wolfe Algorithms for Saddle Point Problems. AISTATS Gauthier Gidel, Tony Jebara, Simon Lacoste-Julien
2016	J	`jnl`	Frank-Wolfe Algorithms for Saddle Point Problems. CoRR Gauthier Gidel, Tony Jebara, Simon Lacoste-Julien