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Vianney Perchet
Vianney Perchet
Crest, ENSAE & Criteo AI Lab
Verified email at normalesup.org - Homepage
Title
Cited by
Cited by
Year
Batched bandit problems
V Perchet, P Rigollet, S Chassang, E Snowberg
2292016
The multi-armed bandit problem with covariates
V Perchet, P Rigollet
1932013
Gaussian process optimization with mutual information
E Contal, V Perchet, N Vayatis
1112014
Bounded regret in stochastic multi-armed bandits
S Bubeck, V Perchet, P Rigollet
Conference on Learning Theory, 122-134, 2013
1112013
SIC-MMAB: Synchronisation involves communication in multiplayer multi-armed bandits
E Boursier, V Perchet
Advances in Neural Information Processing Systems 32, 2019
1002019
Online learning in repeated auctions
J Weed, V Perchet, P Rigollet
Conference on Learning Theory, 1562-1583, 2016
992016
Stochastic bandit models for delayed conversions
C Vernade, O Cappé, V Perchet
arXiv preprint arXiv:1706.09186, 2017
922017
Highly-smooth zero-th order online optimization
F Bach, V Perchet
Conference on Learning Theory, 257-283, 2016
882016
A practical algorithm for multiplayer bandits when arm means vary among players
A Mehrabian, E Boursier, E Kaufmann, V Perchet
International Conference on Artificial Intelligence and Statistics, 1211-1221, 2020
712020
Anytime optimal algorithms in stochastic multi-armed bandits
R Degenne, V Perchet
International Conference on Machine Learning, 1587-1595, 2016
632016
Approachability, regret and calibration; implications and equivalences
V Perchet
arXiv preprint arXiv:1301.2663, 2013
56*2013
Combinatorial semi-bandit with known covariance
R Degenne, V Perchet
Advances in Neural Information Processing Systems 29, 2016
492016
Quantitative analysis of dynamic fault trees based on the coupling of structure functions and Monte Carlo simulation
G Merle, JM Roussel, JJ Lesage, V Perchet, N Vayatis
Quality and Reliability Engineering International 32 (1), 7-18, 2016
422016
Set-valued approachability and online learning with partial monitoring
S Mannor, V Perchet, G Stoltz
The Journal of Machine Learning Research 15 (1), 3247-3295, 2014
40*2014
Learning to bid in revenue-maximizing auctions
T Nedelec, N El Karoui, V Perchet
International Conference on Machine Learning, 4781-4789, 2019
38*2019
Fast rates for bandit optimization with upper-confidence frank-wolfe
Q Berthet, V Perchet
Advances in Neural Information Processing Systems 30, 2017
382017
Internal Regret with Partial Monitoring: Calibration-Based Optimal Algorithms.
V Perchet
Journal of Machine Learning Research 12 (6), 2011
382011
Statistical efficiency of thompson sampling for combinatorial semi-bandits
P Perrault, E Boursier, M Valko, V Perchet
Advances in Neural Information Processing Systems 33, 5429-5440, 2020
362020
Local differential privacy for regret minimization in reinforcement learning
E Garcelon, V Perchet, C Pike-Burke, M Pirotta
Advances in Neural Information Processing Systems 34, 10561-10573, 2021
322021
Approachability of convex sets in games with partial monitoring
V Perchet
Journal of Optimization Theory and Applications 149, 665-677, 2011
312011
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