Pierre Perrault
Pierre Perrault
Inria Sequel, ENS Paris Saclay
Verified email at inria.fr
Title
Cited by
Cited by
Year
Statistical efficiency of thompson sampling for combinatorial semi-bandits
P Perrault, E Boursier, V Perchet, M Valko
arXiv preprint arXiv:2006.06613, 2020
142020
Exploiting structure of uncertainty for efficient matroid semi-bandits
P Perrault, V Perchet, M Valko
International Conference on Machine Learning, 5123-5132, 2019
122019
Budgeted online influence maximization
P Perrault, J Healey, Z Wen, M Valko
International Conference on Machine Learning, 7620-7631, 2020
72020
Finding the bandit in a graph: Sequential search-and-stop
P Perrault, V Perchet, M Valko
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
62019
Covariance-adapting algorithm for semi-bandits with application to sparse outcomes
P Perrault, M Valko, V Perchet
Conference on Learning Theory, 3152-3184, 2020
42020
Active linear regression
X Fontaine, P Perrault, V Perchet
arXiv e-prints, arXiv: 1906.08509, 2019
4*2019
On the Approximation Relationship between Optimizing Ratio of Submodular (RS) and Difference of Submodular (DS) Functions
P Perrault, J Healey, Z Wen, M Valko
arXiv preprint arXiv:2101.01631, 2021
2021
Apprentissage efficient dans les problèmes de semi-bandits stochastiques combinatoires
P Perrault
Université Paris-Saclay, 2020
2020
Efficient Learning in Stochastic Combinatorial Semi-Bandits
P Perrault
Univeristé Paris-Saclay, 2020
2020
ExploitingStructureofUncertaintyforEfficient MatroidSemi-Bandits
P Perrault, V Perchet, M Valko
Supplementary material to “Online A-Optimal Design and Active Linear Regression”
X Fontaine, P Perrault, M Valko, V Perchet
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