引用次数
引用: 2,867
H-指数: 27
I10-指数 : 56
出版物: 150
Brownian Motions and Scrambled Wavelets for Least-Squares Regression
Rémi Munos , Odalric-Ambrym Maillard
13
2
2010
A Finite-Time Analysis of Multi-armed Bandits Problems with Kullback-Leibler Divergences
Rémi Munos , Odalric-Ambrym Maillard , Gilles Stoltz
conference on learning theory 18
70
2011
Complexity versus agreement for many views: co-regularization for multi-view semi-supervised learning
Nicolas Vayatis , Odalric-Ambrym Maillard
algorithmic learning theory 232 -246
1
2009
Optimal Regret Bounds for Selecting the State Representation in Reinforcement Learning
Daniil Ryabko , Odalric-Ambrym Maillard , Ronald Ortner , Phuong Nguyen
international conference on machine learning 543 -551
18
2013
Competing with an Infinite Set of Models in Reinforcement Learning
Daniil Ryabko , Ronald Ortner , Phuong Nguyen , Odalric-Ambrym Maillard
international conference on artificial intelligence and statistics 31 463 -471
8
2013
How hard is my MDP?" The distribution-norm to the rescue"
Odalric-Ambrym Maillard , Timothy A Mann , Shie Mannor
neural information processing systems 27 1835 -1843
54
2014
A note on replacing uniform subsampling by random projections in MCMC for linear regression of tall datasets
Rémi Bardenet , Odalric-Ambrym Maillard
3
2015
Latent Bandits.
Odalric-Ambrym Maillard , Shie Mannor
international conference on machine learning
44
2014
Pliable rejection sampling
Alexandra Carpentier , Michal Valko , Odalric-Ambrym Maillard , Akram Erraqabi
international conference on machine learning 2121 -2129
2
2016
Self-normalization techniques for streaming confident regression
Odalric-Ambrym Maillard
1
2016
Spectral Learning from a Single Trajectory under Finite-State Policies
Odalric-Ambrym Maillard , Borja Balle
international conference on machine learning 361 -370
1
2017
Boundary Crossing for General Exponential Families
Odalric-Ambrym Maillard
algorithmic learning theory 1 151 -184
1
2017
Basic Concentration Properties of Real-Valued Distributions
Odalric-Ambrym Maillard
2017
Practical Open-Loop Optimistic Planning
Odalric-Ambrym Maillard , Edouard Leurent , Edouard Leurent
arXiv: Learning
2019
Sequential change-point detection: Laplace concentration of scan statistics and non-asymptotic delay bounds
Odalric-Ambrym Maillard
algorithmic learning theory 98 610 -632
10
2019
Learning Multiple Markov Chains via Adaptive Allocation
Odalric-Ambrym Maillard , Mohammad Sadegh Talebi
arXiv: Learning
2019
Selecting Near-Optimal Approximate State Representations in Reinforcement Learning
Daniil Ryabko , Odalric-Ambrym Maillard , Ronald Ortner
arXiv: Learning
4
2014
Upper Confidence Reinforcement Learning exploiting state-action equivalence
Odalric-Ambrym Maillard , Mahsa Asadi
1
2018
Streaming kernel regression with provably adaptive mean, variance, and regularization
Odalric-Ambrym Maillard , Joelle Pineau , Audrey Durand
Journal of Machine Learning Research 19 ( 1) 650 -683
11
2018
Efficient tracking of a growing number of experts
Odalric-Ambrym Maillard , Jaouad Mourtada
algorithmic learning theory 76 517 -539
4
2017