← Authors

Dorian Baudry

12 papers · 2020–2024 · 3 conferences · across top CS/AI conferences

Achievements

πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (21) 🐝 Cross-Pollinator (5) 🌈 Renaissance Researcher (5) 🌍 Conference Polyglot (3) 🧭 Keyword Pioneer πŸ† Keyword Champion (2) πŸ—ƒοΈ Keyword Collector (54) πŸ’Ž Century Club (12) πŸ”₯ Unstoppable (5) ⚑ Prolific Year (5)

Conferences

NIPS (8) AISTATS (2) ICML (2)

Top co-authors

Vianney Perchet (5) Emilie Kaufmann (4) Hugo Richard (3) Odalric-ambrym Maillard (3) Yoan Russac (2) Nadav Merlis (2) RΓ©my Degenne (2) Romain Gautron (1) Patrick Saux (1) Rianne de Heide (1)

Keywords

regret bound (4) multi-armed bandit (4) asymptotic optimality (2) thompson sampling (2) multi-arm bandit (2) online learning (2) online algorithm (2) regret minimization (1) reward prediction (1) sample complexity (1) sequential decision (1) stochastic process (1) bandit feedback (1) best arm identification (1) exponential family (1) subsampling methods (1) extreme bandits (1) constraint satisfaction (1) optimal regret (1) kullback-leibler divergence (1)

Papers

Improved learning rates in multi-unit uniform price auctions NIPS 2024
Multi-armed bandits with guaranteed revenue per arm AISTATS 2024
Optimizing the coalition gain in Online Auctions with Greedy Structured Bandits NIPS 2024
Lookback Prophet Inequalities NIPS 2024
The Value of Reward Lookahead in Reinforcement Learning NIPS 2024
Fast Asymptotically Optimal Algorithms for Non-Parametric Stochastic Bandits NIPS 2023
Top Two Algorithms Revisited NIPS 2022
Efficient Algorithms for Extreme Bandits AISTATS 2022
On Limited-Memory Subsampling Strategies for Bandits ICML 2021
From Optimality to Robustness: Adaptive Re-Sampling Strategies in Stochastic Bandits NIPS 2021
Optimal Thompson Sampling strategies for support-aware CVaR bandits ICML 2021
Sub-sampling for Efficient Non-Parametric Bandit Exploration NIPS 2020