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Richard Combes

11 papers · 2014–2024 · 5 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (18) 🧭 Keyword Pioneer 🐝 Cross-Pollinator (15) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (5) πŸƒ Academic Marathon (10) 🐣 Hot Topic Early Bird πŸ’Ž Century Club (11) πŸ”₯ Unstoppable (5)

Conferences

NIPS (5) ALT (2) COLT (2) AISTATS (1) ICML (1)

Top co-authors

Alexandre Proutiere (4) Stefan Magureanu (2) Raymond Zhang (2) Cindy Trinh (2) Mohammad Sadegh Talebi Mazraeh Shahi (1) Claire Vernade (1) Thibaut Cuvelier (1) Emilie Kaufmann (1) Wei Huang (1) Jung-hun Kim (1)

Keywords

regret bound (6) multi-armed bandit (4) stochastic bandit (3) regret lower bound (2) unimodal bandit (2) bayesian inference (2) thompson sampling (2) online optimization (1) posterior distribution (1) posterior sampling (1) ucb algorithm (1) worker reliability (1) adversarial setting (1) polynomial time (1) label aggregation (1) regret minimization (1) upper confidence bound (1) sequential decision (1) streaming algorithm (1) continuous action space (1)

Papers

Thompson Sampling For Combinatorial Bandits: Polynomial Regret and Mismatched Sampling Paradox NIPS 2024
Contextual Linear Bandits under Noisy Features: Towards Bayesian Oracles AISTATS 2023
Towards Optimal Algorithms for Multi-Player Bandits without Collision Sensing Information COLT 2022
On the Suboptimality of Thompson Sampling in High Dimensions NIPS 2021
Asymptotically Optimal Strategies For Combinatorial Semi-Bandits in Polynomial Time ALT 2021
Solving Bernoulli Rank-One Bandits with Unimodal Thompson Sampling ALT 2020
Minimal Exploration in Structured Stochastic Bandits NIPS 2017
A Minimax Optimal Algorithm for Crowdsourcing NIPS 2017
Combinatorial Bandits Revisited NIPS 2015
Lipschitz Bandits: Regret Lower Bound and Optimal Algorithms COLT 2014
Unimodal Bandits: Regret Lower Bounds and Optimal Algorithms ICML 2014