Pierre Perrault

23 papers A* 9A 1Journal 12
YearRankTypeTitle / Venue / Authors
2025 J jnl
Sharper Perturbed-Kullback-Leibler Exponential Tail Bounds for Beta and Dirichlet Distributions.
CoRR
Pierre Perrault
2024 J jnl
A New Bound on the Cumulant Generating Function of Dirichlet Processes.
CoRR
Pierre Perrault, Denis Belomestny, Pierre Ménard, Éric Moulines, Alexey Naumov, Daniil Tiapkin, Michal Valko
2024 A* conf
Demonstration-Regularized RL.
ICLR
Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Alexey Naumov, Pierre Perrault, Michal Valko, Pierre Ménard
2024 J jnl
Limitations of (Procrustes) Alignment in Assessing Multi-Person Human Pose and Shape Estimation.
CoRR
Drazic Martin, Pierre Perrault
2023 J jnl
Demonstration-Regularized RL.
CoRR
Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Alexey Naumov, Pierre Perrault, Michal Valko, Pierre Ménard
2023 A* conf
Fast Rates for Maximum Entropy Exploration.
ICML
Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Pierre Perrault, Yunhao Tang, Michal Valko, Pierre Ménard
2023 J jnl
Fast Rates for Maximum Entropy Exploration.
CoRR
Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Pierre Perrault, Yunhao Tang, Michal Valko, Pierre Ménard
2023 A* conf
Model-free Posterior Sampling via Learning Rate Randomization.
NeurIPS
Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Pierre Perrault, Michal Valko, Pierre Ménard
2023 J jnl
Model-free Posterior Sampling via Learning Rate Randomization.
CoRR
Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Rémi Munos, Alexey Naumov, Pierre Perrault, Michal Valko, Pierre Ménard
2023 J jnl
When Combinatorial Thompson Sampling meets Approximation Regret.
CoRR
Pierre Perrault
2022 A* conf
When Combinatorial Thompson Sampling meets Approximation Regret.
NeurIPS
Pierre Perrault
2021 J jnl
On the Approximation Relationship between Optimizing Ratio of Submodular (RS) and Difference of Submodular (DS) Functions.
CoRR
Pierre Perrault, Jennifer Healey, Zheng Wen, Michal Valko
2021 A* conf
Online A-Optimal Design and Active Linear Regression.
ICML
Xavier Fontaine, Pierre Perrault, Michal Valko, Vianney Perchet
2020 A* conf
Budgeted Online Influence Maximization.
ICML
Pierre Perrault, Jennifer Healey, Zheng Wen, Michal Valko
2020 A* conf
Covariance-adapting algorithm for semi-bandits with application to sparse outcomes.
COLT
Pierre Perrault, Michal Valko, Vianney Perchet
2020 — —
Efficient Learning in Stochastic Combinatorial Semi-Bandits. (Apprentissage Efficient dans les Problèmes de Semi-Bandits Stochastiques Combinatoires).
Pierre Perrault
2020 A* conf
Statistical Efficiency of Thompson Sampling for Combinatorial Semi-Bandits.
NeurIPS
Pierre Perrault, Etienne Boursier, Michal Valko, Vianney Perchet
2020 J jnl
Statistical Efficiency of Thompson Sampling for Combinatorial Semi-Bandits.
CoRR
Pierre Perrault, Etienne Boursier, Vianney Perchet, Michal Valko
2019 J jnl
Active Linear Regression.
CoRR
Xavier Fontaine, Pierre Perrault, Vianney Perchet
2019 J jnl
Exploiting Structure of Uncertainty for Efficient Combinatorial Semi-Bandits.
CoRR
Pierre Perrault, Vianney Perchet, Michal Valko
2019 A* conf
Exploiting structure of uncertainty for efficient matroid semi-bandits.
ICML
Pierre Perrault, Vianney Perchet, Michal Valko
2019 A conf
Finding the bandit in a graph: Sequential search-and-stop.
AISTATS
Pierre Perrault, Vianney Perchet, Michal Valko
2018 J jnl
Finding the Bandit in a Graph: Sequential Search-and-Stop.
CoRR
Pierre Perrault, Vianney Perchet, Michal Valko