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Pierre Perrault
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2020 – today
- 2024
- [c10]Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Alexey Naumov, Pierre Perrault, Michal Valko, Pierre Ménard:
Demonstration-Regularized RL. ICLR 2024 - [i11]Drazic Martin, Pierre Perrault:
Limitations of (Procrustes) Alignment in Assessing Multi-Person Human Pose and Shape Estimation. CoRR abs/2409.16861 (2024) - [i10]Pierre Perrault, Denis Belomestny, Pierre Ménard, Éric Moulines, Alexey Naumov, Daniil Tiapkin, Michal Valko:
A New Bound on the Cumulant Generating Function of Dirichlet Processes. CoRR abs/2409.18621 (2024) - 2023
- [c9]Daniil Tiapkin
, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Pierre Perrault, Yunhao Tang, Michal Valko, Pierre Ménard:
Fast Rates for Maximum Entropy Exploration. ICML 2023: 34161-34221 - [c8]Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Pierre Perrault, Michal Valko, Pierre Ménard:
Model-free Posterior Sampling via Learning Rate Randomization. NeurIPS 2023 - [i9]Pierre Perrault:
When Combinatorial Thompson Sampling meets Approximation Regret. CoRR abs/2302.11182 (2023) - [i8]Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Pierre Perrault, Yunhao Tang, Michal Valko, Pierre Ménard:
Fast Rates for Maximum Entropy Exploration. CoRR abs/2303.08059 (2023) - [i7]Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Alexey Naumov, Pierre Perrault, Michal Valko, Pierre Ménard:
Demonstration-Regularized RL. CoRR abs/2310.17303 (2023) - [i6]Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Pierre Perrault, Michal Valko, Pierre Ménard:
Model-free Posterior Sampling via Learning Rate Randomization. CoRR abs/2310.18186 (2023) - 2022
- [c7]Pierre Perrault:
When Combinatorial Thompson Sampling meets Approximation Regret. NeurIPS 2022 - 2021
- [c6]Xavier Fontaine, Pierre Perrault, Michal Valko, Vianney Perchet:
Online A-Optimal Design and Active Linear Regression. ICML 2021: 3374-3383 - [i5]Pierre Perrault, Jennifer Healey, Zheng Wen, Michal Valko:
On the Approximation Relationship between Optimizing Ratio of Submodular (RS) and Difference of Submodular (DS) Functions. CoRR abs/2101.01631 (2021) - 2020
- [b1]Pierre Perrault:
Efficient Learning in Stochastic Combinatorial Semi-Bandits. (Apprentissage Efficient dans les Problèmes de Semi-Bandits Stochastiques Combinatoires). Paris-Saclay University, France, 2020 - [c5]Pierre Perrault, Michal Valko, Vianney Perchet:
Covariance-adapting algorithm for semi-bandits with application to sparse outcomes. COLT 2020: 3152-3184 - [c4]Pierre Perrault, Jennifer Healey, Zheng Wen, Michal Valko:
Budgeted Online Influence Maximization. ICML 2020: 7620-7631 - [c3]Pierre Perrault, Etienne Boursier, Michal Valko, Vianney Perchet:
Statistical Efficiency of Thompson Sampling for Combinatorial Semi-Bandits. NeurIPS 2020 - [i4]Pierre Perrault, Etienne Boursier, Vianney Perchet, Michal Valko:
Statistical Efficiency of Thompson Sampling for Combinatorial Semi-Bandits. CoRR abs/2006.06613 (2020)
2010 – 2019
- 2019
- [c2]Pierre Perrault, Vianney Perchet, Michal Valko:
Finding the bandit in a graph: Sequential search-and-stop. AISTATS 2019: 1668-1677 - [c1]Pierre Perrault, Vianney Perchet, Michal Valko:
Exploiting structure of uncertainty for efficient matroid semi-bandits. ICML 2019: 5123-5132 - [i3]Pierre Perrault, Vianney Perchet, Michal Valko:
Exploiting Structure of Uncertainty for Efficient Combinatorial Semi-Bandits. CoRR abs/1902.03794 (2019) - [i2]Xavier Fontaine, Pierre Perrault, Vianney Perchet:
Active Linear Regression. CoRR abs/1906.08509 (2019) - 2018
- [i1]Pierre Perrault, Vianney Perchet, Michal Valko:
Finding the Bandit in a Graph: Sequential Search-and-Stop. CoRR abs/1806.02282 (2018)
Coauthor Index
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