| A Variational Inequality Perspective on Generative Adversarial Networks G Gidel, H Berard, G Vignoud, P Vincent, S Lacoste-Julien ICLR 2019 - Proceedings of the Seventh International Conference on Learning …, 2019 | 477 | 2019 |
| Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates S Vaswani, A Mishkin, I Laradji, M Schmidt, G Gidel, S Lacoste-Julien NeurIPS 2019 - Advances in Neural Information Processing Systems, 2019 | 251 | 2019 |
| Negative momentum for improved game dynamics G Gidel, RA Hemmat, M Pezeshki, G Huang, R Lepriol, S Lacoste-Julien, ... AISTATS 2019 - Proceedings of the 22nd International Conference on …, 2019 | 216 | 2019 |
| Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks G Gidel, F Bach, S Lacoste-Julien NeurIPS 2019 - Advances in Neural Information Processing Systems, 3196-3206, 2019 | 189 | 2019 |
| Reducing noise in gan training with variance reduced extragradient T Chavdarova, G Gidel, F Fleuret, S Lacoste-Julien Neurips 2019 - Advances in Neural Information Processing Systems, 2019 | 172 | 2019 |
| Real world games look like spinning tops WM Czarnecki, G Gidel, B Tracey, K Tuyls, S Omidshafiei, D Balduzzi, ... Advances in Neural Information Processing Systems 33, 17443-17454, 2020 | 123 | 2020 |
| A tight and unified analysis of gradient-based methods for a whole spectrum of differentiable games W Azizian, I Mitliagkas, S Lacoste-Julien, G Gidel International conference on artificial intelligence and statistics, 2863-2873, 2020 | 116 | 2020 |
| Extragradient method: O (1/k) last-iterate convergence for monotone variational inequalities and connections with cocoercivity E Gorbunov, N Loizou, G Gidel International Conference on Artificial Intelligence and Statistics, 366-402, 2022 | 103 | 2022 |
| Frank-wolfe algorithms for saddle point problems G Gidel, T Jebara, S Lacoste-Julien AISTATS 2017 - Proceedings of the 20th International Conference on …, 2017 | 98 | 2017 |
| A Closer Look at the Optimization Landscapes of Generative Adversarial Networks H Berard, G Gidel, A Almahairi, P Vincent, S Lacoste-Julien ICLR 2020 - Proceedings of the Eighth International Conference on Learning …, 2020 | 81 | 2020 |
| Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics G Kerg, K Goyette, MP Touzel, G Gidel, E Vorontsov, Y Bengio, G Lajoie NeurIPS 2019 - Advances in Neural Information Processing Systems, 2019 | 78 | 2019 |
| Linear lower bounds and conditioning of differentiable games A Ibrahim, W Azizian, G Gidel, I Mitliagkas International conference on machine learning, 4583-4593, 2020 | 76* | 2020 |
| Finite regret and cycles with fixed step-size via alternating gradient descent-ascent JP Bailey, G Gidel, G Piliouras Conference on Learning Theory, 391-407, 2020 | 73 | 2020 |
| Adversarial example games AJ Bose, G Gidel, H Berard, A Cianflone, P Vincent, S Lacoste-Julien, ... NeurIPS 2020, 2020 | 69 | 2020 |
| Stochastic gradient descent-ascent and consensus optimization for smooth games: Convergence analysis under expected co-coercivity N Loizou, H Berard, G Gidel, I Mitliagkas, S Lacoste-Julien Advances in Neural Information Processing Systems 34, 19095-19108, 2021 | 64 | 2021 |
| Accelerating Smooth Games by Manipulating Spectral Shapes W Azizian, D Scieur, I Mitliagkas, S Lacoste-Julien, G Gidel AISTATS 2020 - Proceedings of the 23rd International Conference on …, 2020 | 58 | 2020 |
| Last-iterate convergence of optimistic gradient method for monotone variational inequalities E Gorbunov, A Taylor, G Gidel Advances in neural information processing systems 35, 21858-21870, 2022 | 57 | 2022 |
| High-probability bounds for stochastic optimization and variational inequalities: the case of unbounded variance A Sadiev, M Danilova, E Gorbunov, S Horváth, G Gidel, P Dvurechensky, ... International Conference on Machine Learning, 29563-29648, 2023 | 55 | 2023 |
| Stochastic extragradient: General analysis and improved rates E Gorbunov, H Berard, G Gidel, N Loizou International Conference on Artificial Intelligence and Statistics, 7865-7901, 2022 | 51 | 2022 |
| Variance reduction is an antidote to byzantines: Better rates, weaker assumptions and communication compression as a cherry on the top E Gorbunov, S Horváth, P Richtárik, G Gidel arXiv preprint arXiv:2206.00529, 2022 | 46 | 2022 |
Simon Lacoste-JulienAssociate Professor - Canada CIFAR AI Chair, University of Montreal / MilaVerified email at iro.umontreal.ca