← Authors

Odalric-ambrym Maillard

38 papers · 2010–2025 · 9 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🌍 Conference Polyglot (9) 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (12) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (15) πŸ—ΊοΈ Taxonomy Completionist (21) 🐺 Lone Wolf (3) πŸ”¬ Deep Specialist (16) 🌱 Topic Pioneer πŸ† Keyword Champion (2) πŸ’Ž Century Club (38) πŸ—ƒοΈ Keyword Collector (54) πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (9) πŸš€ Conference Pioneer ⚑ Prolific Year (5) ❓ The Questioner

Conferences

NIPS (16) ALT (5) ACML (4) ICML (4) AISTATS (3) JMLR (3) COLT (1) ICLR (1) UAI (1)

Top co-authors

Mohammad Sadegh Talebi (5) RΓ©mi Munos (5) Fabien Pesquerel (4) Hassan SABER (3) Emilie Kaufmann (3) Daniil Ryabko (3) Edouard Leurent (3) Ronald Ortner (3) Dorian Baudry (3) Phuong Nguyen (2)

Keywords

regret bound (19) multi-armed bandit (10) markov decision process (10) reinforcement learning (8) regret minimization (5) online learning (4) stochastic optimization (4) upper confidence bound (3) concentration inequality (3) state representation (3) bandit algorithm (3) sample complexity (2) asymptotic optimality (2) active learning (2) regret analysis (2) model-based reinforcement learning (2) change-point detection (2) kullback-leibler divergence (2) reproducing kernel hilbert space (2) exponential family (2)

Papers

Monte-Carlo Tree Search with Uncertainty Propagation via Optimal Transport ICML 2025
CRIMED: Lower and Upper Bounds on Regret for Bandits with Unbounded Stochastic Corruption ALT 2024
Power Mean Estimation in Stochastic Monte-Carlo Tree Search UAI 2024
Logarithmic regret in communicating MDPs: Leveraging known dynamics with bandits ACML 2023
Fast Asymptotically Optimal Algorithms for Non-Parametric Stochastic Bandits NIPS 2023
Exploration in Reward Machines with Low Regret AISTATS 2023
Efficient Change-Point Detection for Tackling Piecewise-Stationary Bandits JMLR 2022
IMED-RL: Regret optimal learning of ergodic Markov decision processes NIPS 2022
Indexed Minimum Empirical Divergence for Unimodal Bandits NIPS 2021
From Optimality to Robustness: Adaptive Re-Sampling Strategies in Stochastic Bandits NIPS 2021
Stochastic bandits with groups of similar arms. NIPS 2021
Stochastic Online Linear Regression: the Forward Algorithm to Replace Ridge NIPS 2021
Learning Value Functions in Deep Policy Gradients using Residual Variance ICLR 2021
Reinforcement Learning in Parametric MDPs with Exponential Families AISTATS 2021
Sub-sampling for Efficient Non-Parametric Bandit Exploration NIPS 2020
Monte-Carlo Graph Search: the Value of Merging Similar States ACML 2020
Robust-Adaptive Control of Linear Systems: beyond Quadratic Costs NIPS 2020
Learning Multiple Markov Chains via Adaptive Allocation NIPS 2019
Regret Bounds for Learning State Representations in Reinforcement Learning NIPS 2019
Model-Based Reinforcement Learning Exploiting State-Action Equivalence ACML 2019
Sequential change-point detection: Laplace concentration of scan statistics and non-asymptotic delay bounds ALT 2019
Budgeted Reinforcement Learning in Continuous State Space NIPS 2019
Streaming kernel regression with provably adaptive mean, variance, and regularization JMLR 2018
Variance-Aware Regret Bounds for Undiscounted Reinforcement Learning in MDPs ALT 2018
Boundary Crossing for General Exponential Families ALT 2017
Efficient tracking of a growing number of experts ALT 2017
Spectral Learning from a Single Trajectory under Finite-State Policies ICML 2017
Latent Bandits. ICML 2014
How hard is my MDP?" The distribution-norm to the rescue" NIPS 2014
Competing with an Infinite Set of Models in Reinforcement Learning AISTATS 2013
Optimal Regret Bounds for Selecting the State Representation in Reinforcement Learning ICML 2013
Hierarchical Optimistic Region Selection driven by Curiosity NIPS 2012
Online allocation and homogeneous partitioning for piecewise constant mean-approximation NIPS 2012
Linear Regression With Random Projections JMLR 2012
Sparse Recovery with Brownian Sensing NIPS 2011
A Finite-Time Analysis of Multi-armed Bandits Problems with Kullback-Leibler Divergences COLT 2011
Selecting the State-Representation in Reinforcement Learning NIPS 2011
Finite-sample Analysis of Bellman Residual Minimization ACML 2010