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ORCIDGauthier Gidel
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2020 – today
- 2024
[j1]Junhyung Lyle Kim, Gauthier Gidel, Anastasios Kyrillidis, Fabian Pedregosa:
When is Momentum Extragradient Optimal? A Polynomial-Based Analysis. Trans. Mach. Learn. Res. 2024 (2024)- [c53]Damien Ferbach, Baptiste Goujaud, Gauthier Gidel, Aymeric Dieuleveut:
Proving Linear Mode Connectivity of Neural Networks via Optimal Transport. AISTATS 2024: 3853-3861 - [c52]Ruslan Nazykov, Aleksandr Shestakov
, Vladimir Solodkin, Aleksandr Beznosikov, Gauthier Gidel, Alexander V. Gasnikov:
Stochastic Frank-Wolfe: Unified Analysis and Zoo of Special Cases. AISTATS 2024: 4870-4878 - [c51]Quentin Bertrand, Avishek Joey Bose, Alexandre Duplessis, Marco Jiralerspong, Gauthier Gidel:
On the Stability of Iterative Retraining of Generative Models on their own Data. ICLR 2024 - [c50]Marco Jiralerspong, Bilun Sun, Danilo Vucetic, Tianyu Zhang, Yoshua Bengio, Gauthier Gidel, Nikolay Malkin:
Expected flow networks in stochastic environments and two-player zero-sum games. ICLR 2024 - [c49]Roman Pogodin, Jonathan Cornford, Arna Ghosh, Gauthier Gidel, Guillaume Lajoie, Blake Aaron Richards:
Synaptic Weight Distributions Depend on the Geometry of Plasticity. ICLR 2024 - [c48]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:
Iterated Denoising Energy Matching for Sampling from Boltzmann Densities. ICML 2024 - [c47]Aleksandr Beznosikov, David Dobre, Gauthier Gidel:
Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features. ICML 2024 - [c46]Eduard Gorbunov, Abdurakhmon Sadiev, Marina Danilova, Samuel Horváth, Gauthier Gidel, Pavel E. Dvurechensky, Alexander V. Gasnikov, Peter Richtárik:
High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise. ICML 2024 - [c45]Safwan Hossain, Andjela Mladenovic, Yiling Chen, Gauthier Gidel:
A Persuasive Approach to Combating Misinformation. ICML 2024 - [c44]Michael Przystupa, Gauthier Gidel, Matthew E. Taylor, Martin Jägersand, Justus H. Piater, Samuele Tosatto:
Local Linearity is All You Need (in Data-Driven Teleoperation). IROS 2024: 12148-12155 - [c43]Leo Schwinn, David Dobre, Sophie Xhonneux, Gauthier Gidel, Stephan Günnemann:
Soft Prompt Threats: Attacking Safety Alignment and Unlearning in Open-Source LLMs through the Embedding Space. NeurIPS 2024 - [c42]Sophie Xhonneux, Alessandro Sordoni, Stephan Günnemann, Gauthier Gidel, Leo Schwinn:
Efficient Adversarial Training in LLMs with Continuous Attacks. NeurIPS 2024 - [i66]Sophie Xhonneux, David Dobre, Jian Tang, Gauthier Gidel, Dhanya Sridhar:
In-Context Learning Can Re-learn Forbidden Tasks. CoRR abs/2402.05723 (2024) - [i65]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:
Iterated Denoising Energy Matching for Sampling from Boltzmann Densities. CoRR abs/2402.06121 (2024) - [i64]Leo Schwinn, David Dobre, Sophie Xhonneux, Gauthier Gidel, Stephan Günnemann:
Soft Prompt Threats: Attacking Safety Alignment and Unlearning in Open-Source LLMs through the Embedding Space. CoRR abs/2402.09063 (2024) - [i63]Sophie Xhonneux, Alessandro Sordoni, Stephan Günnemann, Gauthier Gidel, Leo Schwinn:
Efficient Adversarial Training in LLMs with Continuous Attacks. CoRR abs/2405.15589 (2024) - [i62]Seanie Lee, Minsu Kim, Lynn Cherif, David Dobre, Juho Lee, Sung Ju Hwang, Kenji Kawaguchi, Gauthier Gidel, Yoshua Bengio, Nikolay Malkin, Moksh Jain:
Learning diverse attacks on large language models for robust red-teaming and safety tuning. CoRR abs/2405.18540 (2024) - [i61]Damien Ferbach, Quentin Bertrand, Avishek Joey Bose, Gauthier Gidel:
Self-Consuming Generative Models with Curated Data Provably Optimize Human Preferences. CoRR abs/2407.09499 (2024) - [i60]António Góis, Mehrnaz Mofakhami, Fernando P. Santos, Simon Lacoste-Julien, Gauthier Gidel:
Performative Prediction on Games and Mechanism Design. CoRR abs/2408.05146 (2024) - [i59]Marco Jiralerspong, Thomas Jiralerspong, Vedant Shah, Dhanya Sridhar, Gauthier Gidel:
General Causal Imputation via Synthetic Interventions. CoRR abs/2410.20647 (2024) - [i58]Michael Przystupa, Gauthier Gidel, Matthew E. Taylor, Martin Jägersand, Justus H. Piater, Samuele Tosatto:
Investigating the Benefits of Nonlinear Action Maps in Data-Driven Teleoperation. CoRR abs/2410.21406 (2024) - [i57]Ryan D'Orazio, Danilo Vucetic, Zichu Liu, Junhyung Lyle Kim, Ioannis Mitliagkas, Gauthier Gidel:
Solving Hidden Monotone Variational Inequalities with Surrogate Losses. CoRR abs/2411.05228 (2024) - [i56]Pedram Khorsandi, Rushil Gupta, Mehrnaz Mofakhami, Simon Lacoste-Julien, Gauthier Gidel:
Tight Lower Bounds and Improved Convergence in Performative Prediction. CoRR abs/2412.03671 (2024) - 2023
- [c41]Quentin Bertrand, Wojciech Marian Czarnecki, Gauthier Gidel:
On the Limitations of the Elo, Real-World Games are Transitive, not Additive. AISTATS 2023: 2905-2921 - [c40]Mehrnaz Mofakhami, Ioannis Mitliagkas, Gauthier Gidel:
Performative Prediction with Neural Networks. AISTATS 2023: 11079-11093 - [c39]Leo Schwinn, David Dobre, Stephan Günnemann, Gauthier Gidel:
Adversarial Attacks and Defenses in Large Language Models: Old and New Threats. ICBINB 2023: 103-117 - [c38]Damien Ferbach, Christos Tsirigotis, Gauthier Gidel, Avishek Joey Bose:
A General Framework For Proving The Equivariant Strong Lottery Ticket Hypothesis. ICLR 2023 - [c37]Eduard Gorbunov, Samuel Horváth, Peter Richtárik, Gauthier Gidel:
Variance Reduction is an Antidote to Byzantines: Better Rates, Weaker Assumptions and Communication Compression as a Cherry on the Top. ICLR 2023 - [c36]Eduard Gorbunov, Adrien B. Taylor, Samuel Horváth, Gauthier Gidel:
Convergence of Proximal Point and Extragradient-Based Methods Beyond Monotonicity: the Case of Negative Comonotonicity. ICML 2023: 11614-11641 - [c35]Chris Junchi Li, Huizhuo Yuan, Gauthier Gidel, Quanquan Gu, Michael I. Jordan:
Nesterov Meets Optimism: Rate-Optimal Separable Minimax Optimization. ICML 2023: 20351-20383 - [c34]Abdurakhmon Sadiev, Marina Danilova, Eduard Gorbunov, Samuel Horváth, Gauthier Gidel, Pavel E. Dvurechensky, Alexander V. Gasnikov, Peter Richtárik:
High-Probability Bounds for Stochastic Optimization and Variational Inequalities: the Case of Unbounded Variance. ICML 2023: 29563-29648 - [c33]Marco Jiralerspong, Avishek Joey Bose, Ian Gemp, Chongli Qin, Yoram Bachrach, Gauthier Gidel:
Feature Likelihood Score: Evaluating the Generalization of Generative Models Using Samples. NeurIPS 2023 - [c32]Angela Yuan, Chris Junchi Li, Gauthier Gidel, Michael I. Jordan, Quanquan Gu, Simon S. Du:
Optimal Extragradient-Based Algorithms for Stochastic Variational Inequalities with Separable Structure. NeurIPS 2023 - [i55]Abdurakhmon Sadiev, Marina Danilova, Eduard Gorbunov, Samuel Horváth, Gauthier Gidel, Pavel E. Dvurechensky, Alexander V. Gasnikov, Peter Richtárik:
High-Probability Bounds for Stochastic Optimization and Variational Inequalities: the Case of Unbounded Variance. CoRR abs/2302.00999 (2023) - [i54]Marco Jiralerspong, Avishek Joey Bose, Gauthier Gidel:
Feature Likelihood Score: Evaluating Generalization of Generative Models Using Samples. CoRR abs/2302.04440 (2023) - [i53]Mehrnaz Mofakhami, Ioannis Mitliagkas, Gauthier Gidel:
Performative Prediction with Neural Networks. CoRR abs/2304.06879 (2023) - [i52]Aleksandr Beznosikov, David Dobre, Gauthier Gidel:
Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features. CoRR abs/2304.11737 (2023) - [i51]Thomas Altstidl, David Dobre, Björn M. Eskofier, Gauthier Gidel, Leo Schwinn:
Raising the Bar for Certified Adversarial Robustness with Diffusion Models. CoRR abs/2305.10388 (2023) - [i50]Roman Pogodin, Jonathan Cornford, Arna Ghosh, Gauthier Gidel, Guillaume Lajoie, Blake A. Richards:
Synaptic Weight Distributions Depend on the Geometry of Plasticity. CoRR abs/2305.19394 (2023) - [i49]Juan Ramirez, Rohan Sukumaran, Quentin Bertrand, Gauthier Gidel:
Omega: Optimistic EMA Gradients. CoRR abs/2306.07905 (2023) - [i48]Marco Jiralerspong, Gauthier Gidel:
AI4GCC - Track 3: Consumption and the Challenges of Multi-Agent RL. CoRR abs/2308.05260 (2023) - [i47]Quentin Bertrand, Avishek Joey Bose, Alexandre Duplessis, Marco Jiralerspong, Gauthier Gidel:
On the Stability of Iterative Retraining of Generative Models on their own Data. CoRR abs/2310.00429 (2023) - [i46]Eduard Gorbunov, Abdurakhmon Sadiev, Marina Danilova, Samuel Horváth, Gauthier Gidel, Pavel E. Dvurechensky, Alexander V. Gasnikov, Peter Richtárik:
High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise. CoRR abs/2310.01860 (2023) - [i45]Marco Jiralerspong, Bilun Sun, Danilo Vucetic, Tianyu Zhang, Yoshua Bengio, Gauthier Gidel, Nikolay Malkin:
Expected flow networks in stochastic environments and two-player zero-sum games. CoRR abs/2310.02779 (2023) - [i44]Safwan Hossain, Andjela Mladenovic, Yiling Chen, Gauthier Gidel:
A Persuasive Approach to Combating Misinformation. CoRR abs/2310.12065 (2023) - [i43]Damien Ferbach, Baptiste Goujaud, Gauthier Gidel, Aymeric Dieuleveut:
Proving Linear Mode Connectivity of Neural Networks via Optimal Transport. CoRR abs/2310.19103 (2023) - [i42]Leo Schwinn, David Dobre, Stephan Günnemann, Gauthier Gidel:
Adversarial Attacks and Defenses in Large Language Models: Old and New Threats. CoRR abs/2310.19737 (2023) - [i41]Quentin Bertrand, Juan Duque, Emilio Calvano, Gauthier Gidel:
Q-learners Can Provably Collude in the Iterated Prisoner's Dilemma. CoRR abs/2312.08484 (2023) - 2022
- [c31]Eduard Gorbunov, Nicolas Loizou, Gauthier Gidel:
Extragradient Method: O(1/K) Last-Iterate Convergence for Monotone Variational Inequalities and Connections With Cocoercivity. AISTATS 2022: 366-402 - [c30]Eduard Gorbunov, Hugo Berard, Gauthier Gidel, Nicolas Loizou:
Stochastic Extragradient: General Analysis and Improved Rates. AISTATS 2022: 7865-7901 - [c29]Chris Junchi Li, Yaodong Yu, Nicolas Loizou, Gauthier Gidel, Yi Ma, Nicolas Le Roux, Michael I. Jordan:
On the Convergence of Stochastic Extragradient for Bilinear Games using Restarted Iteration Averaging. AISTATS 2022: 9793-9826 - [c28]Andjela Mladenovic, Avishek Joey Bose, Hugo Berard, William L. Hamilton, Simon Lacoste-Julien, Pascal Vincent, Gauthier Gidel:
Online Adversarial Attacks. ICLR 2022 - [c27]Andjela Mladenovic, Iosif Sakos, Gauthier Gidel, Georgios Piliouras:
Generalized Natural Gradient Flows in Hidden Convex-Concave Games and GANs. ICLR 2022 - [c26]Leonardo Cunha, Gauthier Gidel, Fabian Pedregosa, Damien Scieur, Courtney Paquette:
Only tails matter: Average-Case Universality and Robustness in the Convex Regime. ICML 2022: 4474-4491 - [c25]Quentin Bertrand, Quentin Klopfenstein, Pierre-Antoine Bannier, Gauthier Gidel, Mathurin Massias:
Beyond L1: Faster and Better Sparse Models with skglm. NeurIPS 2022 - [c24]Eduard Gorbunov, Marina Danilova, David Dobre, Pavel E. Dvurechenskii, Alexander V. Gasnikov, Gauthier Gidel:
Clipped Stochastic Methods for Variational Inequalities with Heavy-Tailed Noise. NeurIPS 2022 - [c23]Eduard Gorbunov, Adrien B. Taylor, Gauthier Gidel:
Last-Iterate Convergence of Optimistic Gradient Method for Monotone Variational Inequalities. NeurIPS 2022 - [c22]Damien Scieur, Gauthier Gidel, Quentin Bertrand, Fabian Pedregosa:
The Curse of Unrolling: Rate of Differentiating Through Optimization. NeurIPS 2022 - [i40]Quentin Bertrand, Quentin Klopfenstein, Pierre-Antoine Bannier, Gauthier Gidel, Mathurin Massias:
Beyond L1: Faster and Better Sparse Models with skglm. CoRR abs/2204.07826 (2022) - [i39]Alice Baird, Panagiotis Tzirakis, Gauthier Gidel, Marco Jiralerspong, Eilif B. Muller, Kory W. Mathewson, Björn W. Schuller, Erik Cambria, Dacher Keltner, Alan Cowen:
The ICML 2022 Expressive Vocalizations Workshop and Competition: Recognizing, Generating, and Personalizing Vocal Bursts. CoRR abs/2205.01780 (2022) - [i38]Eduard Gorbunov, Samuel Horváth, Peter Richtárik, Gauthier Gidel:
Variance Reduction is an Antidote to Byzantines: Better Rates, Weaker Assumptions and Communication Compression as a Cherry on the Top. CoRR abs/2206.00529 (2022) - [i37]Eduard Gorbunov, Marina Danilova, David Dobre, Pavel E. Dvurechensky, Alexander V. Gasnikov, Gauthier Gidel:
Clipped Stochastic Methods for Variational Inequalities with Heavy-Tailed Noise. CoRR abs/2206.01095 (2022) - [i36]Damien Ferbach, Christos Tsirigotis, Gauthier Gidel, Avishek Joey Bose:
A General Framework For Proving The Equivariant Strong Lottery Ticket Hypothesis. CoRR abs/2206.04270 (2022) - [i35]Simon S. Du, Gauthier Gidel, Michael I. Jordan, Chris Junchi Li:
Optimal Extragradient-Based Bilinearly-Coupled Saddle-Point Optimization. CoRR abs/2206.08573 (2022) - [i34]Leonardo Cunha, Gauthier Gidel, Fabian Pedregosa, Damien Scieur, Courtney Paquette:
Only Tails Matter: Average-Case Universality and Robustness in the Convex Regime. CoRR abs/2206.09901 (2022) - [i33]Quentin Bertrand, Wojciech Marian Czarnecki, Gauthier Gidel:
On the Limitations of Elo: Real-World Games, are Transitive, not Additive. CoRR abs/2206.12301 (2022) - [i32]Marco Jiralerspong, Gauthier Gidel:
Generating Diverse Vocal Bursts with StyleGAN2 and MEL-Spectrograms. CoRR abs/2206.12563 (2022) - [i31]Alice Baird, Panagiotis Tzirakis, Gauthier Gidel, Marco Jiralerspong, Eilif B. Muller, Kory W. Mathewson, Björn W. Schuller, Erik Cambria, Dacher Keltner, Alan Cowen:
Proceedings of the ICML 2022 Expressive Vocalizations Workshop and Competition: Recognizing, Generating, and Personalizing Vocal Bursts. CoRR abs/2207.06958 (2022) - [i30]Samy Jelassi, David Dobre, Arthur Mensch, Yuanzhi Li, Gauthier Gidel:
Dissecting adaptive methods in GANs. CoRR abs/2210.04319 (2022) - [i29]Chris Junchi Li, Angela Yuan, Gauthier Gidel, Michael I. Jordan:
Nesterov Meets Optimism: Rate-Optimal Optimistic-Gradient-Based Method for Stochastic Bilinearly-Coupled Minimax Optimization. CoRR abs/2210.17550 (2022) - [i28]Junhyung Lyle Kim, Gauthier Gidel, Anastasios Kyrillidis, Fabian Pedregosa:
Extragradient with Positive Momentum is Optimal for Games with Cross-Shaped Jacobian Spectrum. CoRR abs/2211.04659 (2022) - 2021
- [c21]Gauthier Gidel, David Balduzzi, Wojciech Czarnecki, Marta Garnelo, Yoram Bachrach:
A Limited-Capacity Minimax Theorem for Non-Convex Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets. AISTATS 2021: 2548-2556 - [c20]Marta Garnelo, Wojciech Marian Czarnecki, Siqi Liu, Dhruva Tirumala, Junhyuk Oh, Gauthier Gidel, Hado van Hasselt, David Balduzzi:
Pick Your Battles: Interaction Graphs as Population-Level Objectives for Strategic Diversity. AAMAS 2021: 1501-1503 - [c19]Sébastien Bubeck, Yeshwanth Cherapanamjeri, Gauthier Gidel, Remi Tachet des Combes:
A single gradient step finds adversarial examples on random two-layers neural networks. NeurIPS 2021: 10081-10091 - [c18]Nicolas Loizou, Hugo Berard, Gauthier Gidel, Ioannis Mitliagkas, Simon Lacoste-Julien:
Stochastic Gradient Descent-Ascent and Consensus Optimization for Smooth Games: Convergence Analysis under Expected Co-coercivity. NeurIPS 2021: 19095-19108 - [i27]Andjela Mladenovic, Avishek Joey Bose, Hugo Berard, William L. Hamilton, Simon Lacoste-Julien, Pascal Vincent, Gauthier Gidel:
Online Adversarial Attacks. CoRR abs/2103.02014 (2021) - [i26]Sébastien Bubeck, Yeshwanth Cherapanamjeri, Gauthier Gidel, Rémi Tachet des Combes:
A single gradient step finds adversarial examples on random two-layers neural networks. CoRR abs/2104.03863 (2021) - [i25]Nicolas Loizou, Hugo Berard, Gauthier Gidel, Ioannis Mitliagkas, Simon Lacoste-Julien:
Stochastic Gradient Descent-Ascent and Consensus Optimization for Smooth Games: Convergence Analysis under Expected Co-coercivity. CoRR abs/2107.00052 (2021) - [i24]Chris Junchi Li, Yaodong Yu, Nicolas Loizou, Gauthier Gidel, Yi Ma, Nicolas Le Roux, Michael I. Jordan:
On the Convergence of Stochastic Extragradient for Bilinear Games with Restarted Iteration Averaging. CoRR abs/2107.00464 (2021) - [i23]Marta Garnelo, Wojciech Marian Czarnecki, Siqi Liu, Dhruva Tirumala, Junhyuk Oh, Gauthier Gidel, Hado van Hasselt, David Balduzzi:
Pick Your Battles: Interaction Graphs as Population-Level Objectives for Strategic Diversity. CoRR abs/2110.04041 (2021) - [i22]Eduard Gorbunov, Nicolas Loizou, Gauthier Gidel:
Extragradient Method: O(1/K) Last-Iterate Convergence for Monotone Variational Inequalities and Connections With Cocoercivity. CoRR abs/2110.04261 (2021) - [i21]Manuela Girotti, Ioannis Mitliagkas, Gauthier Gidel:
Convergence Analysis and Implicit Regularization of Feedback Alignment for Deep Linear Networks. CoRR abs/2110.10815 (2021) - [i20]M. Mehdi Afsar, Eric Park, Étienne Paquette, Gauthier Gidel, Kory W. Mathewson, Eilif B. Muller:
Generating Diverse Realistic Laughter for Interactive Art. CoRR abs/2111.03146 (2021) - [i19]Eduard Gorbunov, Hugo Berard, Gauthier Gidel, Nicolas Loizou:
Stochastic Extragradient: General Analysis and Improved Rates. CoRR abs/2111.08611 (2021) - 2020
- [c17]Waïss Azizian, Damien Scieur, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel:
Accelerating Smooth Games by Manipulating Spectral Shapes. AISTATS 2020: 1705-1715 - [c16]Waïss Azizian, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel:
A Tight and Unified Analysis of Gradient-Based Methods for a Whole Spectrum of Differentiable Games. AISTATS 2020: 2863-2873 - [c15]James P. Bailey, Gauthier Gidel, Georgios Piliouras:
Finite Regret and Cycles with Fixed Step-Size via Alternating Gradient Descent-Ascent. COLT 2020: 391-407 - [c14]Hugo Berard, Gauthier Gidel, Amjad Almahairi, Pascal Vincent, Simon Lacoste-Julien:
A Closer Look at the Optimization Landscapes of Generative Adversarial Networks. ICLR 2020 - [c13]Adam Ibrahim, Waïss Azizian, Gauthier Gidel, Ioannis Mitliagkas:
Linear Lower Bounds and Conditioning of Differentiable Games. ICML 2020: 4583-4593 - [c12]Avishek Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien, William L. Hamilton:
Adversarial Example Games. NeurIPS 2020 - [c11]Wojciech M. Czarnecki, Gauthier Gidel, Brendan D. Tracey, Karl Tuyls, Shayegan Omidshafiei, David Balduzzi, Max Jaderberg:
Real World Games Look Like Spinning Tops. NeurIPS 2020 - [i18]Waïss Azizian, Damien Scieur, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel:
Accelerating Smooth Games by Manipulating Spectral Shapes. CoRR abs/2001.00602 (2020) - [i17]Gauthier Gidel, David Balduzzi, Wojciech Marian Czarnecki, Marta Garnelo, Yoram Bachrach:
Minimax Theorem for Latent Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets. CoRR abs/2002.05820 (2020) - [i16]Wojciech Marian Czarnecki, Gauthier Gidel, Brendan D. Tracey, Karl Tuyls, Shayegan Omidshafiei, David Balduzzi, Max Jaderberg:
Real World Games Look Like Spinning Tops. CoRR abs/2004.09468 (2020) - [i15]Avishek Joey Bose, Gauthier Gidel, Hugo Berard, Andre Cianflone, Pascal Vincent, Simon Lacoste-Julien, William L. Hamilton:
Adversarial Example Games. CoRR abs/2007.00720 (2020)
2010 – 2019
- 2019
- [c10]Gauthier Gidel, Reyhane Askari Hemmat, Mohammad Pezeshki, Rémi Le Priol, Gabriel Huang, Simon Lacoste-Julien, Ioannis Mitliagkas:
Negative Momentum for Improved Game Dynamics. AISTATS 2019: 1802-1811 - [c9]Gauthier Gidel, Hugo Berard, Gaëtan Vignoud, Pascal Vincent, Simon Lacoste-Julien:
A Variational Inequality Perspective on Generative Adversarial Networks. ICLR (Poster) 2019 - [c8]Tatjana Chavdarova, Gauthier Gidel, François Fleuret, Simon Lacoste-Julien:
Reducing Noise in GAN Training with Variance Reduced Extragradient. NeurIPS 2019: 391-401 - [c7]Gauthier Gidel, Francis R. Bach, Simon Lacoste-Julien:
Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks. NeurIPS 2019: 3196-3206 - [c6]Sharan Vaswani, Aaron Mishkin, Issam H. Laradji, Mark Schmidt, Gauthier Gidel, Simon Lacoste-Julien:
Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates. NeurIPS 2019: 3727-3740 - [c5]Giancarlo Kerg, Kyle Goyette, Maximilian Puelma Touzel, Gauthier Gidel, Eugene Vorontsov, Yoshua Bengio, Guillaume Lajoie:
Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics. NeurIPS 2019: 13591-13601 - [i14]Tatjana Chavdarova, Gauthier Gidel, François Fleuret, Simon Lacoste-Julien:
Reducing Noise in GAN Training with Variance Reduced Extragradient. CoRR abs/1904.08598 (2019) - [i13]Gauthier Gidel, Francis R. Bach, Simon Lacoste-Julien:
Implicit Regularization of Discrete Gradient Dynamics in Deep Linear Neural Networks. CoRR abs/1904.13262 (2019) - [i12]Sharan Vaswani, Aaron Mishkin, Issam H. Laradji, Mark Schmidt, Gauthier Gidel, Simon Lacoste-Julien:
Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates. CoRR abs/1905.09997 (2019) - [i11]Giancarlo Kerg, Kyle Goyette, Maximilian Puelma Touzel, Gauthier Gidel, Eugene Vorontsov, Yoshua Bengio, Guillaume Lajoie:
Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics. CoRR abs/1905.12080 (2019) - [i10]Hugo Berard, Gauthier Gidel, Amjad Almahairi, Pascal Vincent, Simon Lacoste-Julien:
A Closer Look at the Optimization Landscapes of Generative Adversarial Networks. CoRR abs/1906.04848 (2019) - [i9]Waïss Azizian, Ioannis Mitliagkas, Simon Lacoste-Julien, Gauthier Gidel:
A Tight and Unified Analysis of Extragradient for a Whole Spectrum of Differentiable Games. CoRR abs/1906.05945 (2019) - [i8]Adam Ibrahim, Waïss Azizian, Gauthier Gidel, Ioannis Mitliagkas:
Lower Bounds and Conditioning of Differentiable Games. CoRR abs/1906.07300 (2019) - [i7]James P. Bailey, Gauthier Gidel, Georgios Piliouras:
Finite Regret and Cycles with Fixed Step-Size via Alternating Gradient Descent-Ascent. CoRR abs/1907.04392 (2019) - 2018
- [c4]Gauthier Gidel, Fabian Pedregosa, Simon Lacoste-Julien:
Frank-Wolfe Splitting via Augmented Lagrangian Method. AISTATS 2018: 1456-1465 - [c3]Gabriel Huang, Hugo Berard, Ahmed Touati, Gauthier Gidel, Pascal Vincent, Simon Lacoste-Julien:
Parametric Adversarial Divergences are Good Task Losses for Generative Modeling. ICLR (Workshop) 2018 - [c2]Fabian Pedregosa, Gauthier Gidel:
Adaptive Three Operator Splitting. ICML 2018: 4082-4091 - [i6]Gauthier Gidel, Hugo Berard, Pascal Vincent, Simon Lacoste-Julien:
A Variational Inequality Perspective on Generative Adversarial Nets. CoRR abs/1802.10551 (2018) - [i5]Fabian Pedregosa, Gauthier Gidel:
Adaptive Three Operator Splitting. CoRR abs/1804.02339 (2018) - [i4]Gauthier Gidel, Fabian Pedregosa, Simon Lacoste-Julien:
Frank-Wolfe Splitting via Augmented Lagrangian Method. CoRR abs/1804.03176 (2018) - [i3]Gauthier Gidel, Reyhane Askari Hemmat, Mohammad Pezeshki, Gabriel Huang, Rémi Le Priol, Simon Lacoste-Julien, Ioannis Mitliagkas:
Negative Momentum for Improved Game Dynamics. CoRR abs/1807.04740 (2018) - 2017
- [c1]Gauthier Gidel, Tony Jebara, Simon Lacoste-Julien:
Frank-Wolfe Algorithms for Saddle Point Problems. AISTATS 2017: 362-371 - [i2]Gabriel Huang, Gauthier Gidel, Hugo Berard, Ahmed Touati, Simon Lacoste-Julien:
Adversarial Divergences are Good Task Losses for Generative Modeling. CoRR abs/1708.02511 (2017) - 2016
- [i1]Gauthier Gidel, Tony Jebara, Simon Lacoste-Julien:
Frank-Wolfe Algorithms for Saddle Point Problems. CoRR abs/1610.07797 (2016)
Coauthor Index
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