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Hugo Berard
Hugo Berard
PhD student, MILA, University of Montreal
Geverifieerd e-mailadres voor umontreal.ca - Homepage
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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 - Seventh International Conference on Learning Representations, 2018
4742018
A closer look at the optimization landscapes of generative adversarial networks
H Berard, G Gidel, A Almahairi, P Vincent, S Lacoste-Julien
ICLR 2020 - Eighth International Conference on Learning Representations, 2019
782019
Adversarial Example Games
AJ Bose, G Gidel, H Berard, A Cianflone, P Vincent, S Lacoste-Julien, ...
NeurIPS 2020 - Advances in Neural Information Processing Systems 34, 2020
672020
Stochastic hamiltonian gradient methods for smooth games
N Loizou, H Berard, A Jolicoeur-Martineau, P Vincent, S Lacoste-Julien, ...
ICML 2020 - Proceedings of the 37th International Conference on Machine …, 2020
572020
Stochastic gradient descent-ascent: Unified theory and new efficient methods
A Beznosikov, E Gorbunov, H Berard, N Loizou
AISTATS 2023 - International Conference on Artificial Intelligence and …, 2023
562023
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
NeurIPS 2021 - Advances in Neural Information Processing Systems 35, 2021
552021
Stochastic extragradient: General analysis and improved rates
E Gorbunov, H Berard, G Gidel, N Loizou
AISTATS 2022 - International Conference on Artificial Intelligence and …, 2022
422022
Parametric adversarial divergences are good task losses for generative modeling
G Huang, H Berard, A Touati, G Gidel, P Vincent, S Lacoste-Julien
18*2018
Online adversarial attacks
A Mladenovic, AJ Bose, H Berard, WL Hamilton, S Lacoste-Julien, ...
ICLR 2022 - International Conference on Learning Representations, 2021
142021
Adversarial divergences are good task losses for generative modeling
G Huang, G Gidel, H Berard, A Touati, S Lacoste-Julien
arXiv preprint arXiv:1708.02511, 2017
22017
AI-EDI-SPACE: A Co-designed Dataset for Evaluating the Quality of Public Spaces
S Gowaikar, H Berard, R Mushkani, EB Marchand, T Ammar, S Koseki
arXiv preprint arXiv:2411.00956, 2024
2024
From Efficiency to Equity: Measuring Fairness in Preference Learning
S Gowaikar, H Berard, R Mushkani, S Koseki
arXiv preprint arXiv:2410.18841, 2024
2024
Evaluation algorithmique inclusive de la qualité des espaces publics
S Koseki, T Ammar, RA Mushkani, H Berard, S Tannir
SHS Web of Conferences 203, 01005, 2024
2024
Adversarial games in machine learning: challenges and applications
H Berard
2023
MID-Space: Aligning Diverse Communities' Needs to Inclusive Public Spaces
S Nayak, R Mushkani, H Berard, A Cohen, S Koseki, H Bertrand
Pluralistic Alignment Workshop at NeurIPS 2024, 0
A Distributional Robustness Perspective on Adversarial Training with the -Wasserstein Distance
C Regniez, G Gidel, H Berard
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Artikelen 1–16