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Gauthier Gidel
Gauthier Gidel
Assistant professor at Mila, University of Montréal (DIRO)
Zweryfikowany adres z umontreal.ca - Strona główna
Tytuł
Cytowane przez
Cytowane przez
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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
4772019
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
2512019
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
2162019
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
1892019
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
1722019
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
1232020
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
1162020
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
1042022
Frank-wolfe algorithms for saddle point problems
G Gidel, T Jebara, S Lacoste-Julien
AISTATS 2017 - Proceedings of the 20th International Conference on …, 2017
982017
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
812020
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
782019
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
732020
Adversarial example games
AJ Bose, G Gidel, H Berard, A Cianflone, P Vincent, S Lacoste-Julien, ...
NeurIPS 2020, 2020
692020
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
642021
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
582022
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
582020
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
552023
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
512022
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
462022
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