← Authors

Alexandre Proutiere

33 papers · 2013–2025 · 6 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (13) 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (12) 🌈 Renaissance Researcher (7) πŸƒ Academic Marathon (12) 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (6) πŸ† Keyword Champion (2) πŸ—ƒοΈ Keyword Collector (112) πŸš€ Conference Pioneer πŸ’Ž Century Club (33) πŸ”₯ Unstoppable (13) πŸ“ˆ Trend Setter ⚑ Prolific Year (8)

Conferences

NIPS (18) ICML (8) AISTATS (3) COLT (2) AAAI (1) ALT (1)

Top co-authors

Se-Young Yun (9) Yassir Jedra (7) Kaito Ariu (5) Po-An Wang (5) Richard Combes (4) Alessio Russo (3) Stefan Stojanovic (3) Ruo-Chun Tzeng (3) marc lelarge (3) Stefan Magureanu (2)

Keywords

sample complexity (9) regret bound (7) multi-armed bandit (7) stochastic bandit (5) reinforcement learning (4) community detection (4) markov decision process (4) best arm identification (4) adaptive sampling (4) stochastic block model (3) spectral method (3) active learning (2) graph clustering (2) clustering algorithm (2) streaming algorithm (2) matrix estimation (2) network clustering (2) network analysis (2) regret minimization (2) mean field (2)

Papers

Revisiting Instance-Optimal Cluster Recovery in the Labeled Stochastic Block Model ICML 2025
Model-free Low-Rank Reinforcement Learning via Leveraged Entry-wise Matrix Estimation NIPS 2024
Conformal Predictions under Markovian Data ICML 2024
On Universally Optimal Algorithms for A/B Testing ICML 2024
Low-Rank Bandits via Tight Two-to-Infinity Singular Subspace Recovery ICML 2024
Spectral Entry-wise Matrix Estimation for Low-Rank Reinforcement Learning NIPS 2023
Best Arm Identification with Fixed Budget: A Large Deviation Perspective NIPS 2023
Closing the Computational-Statistical Gap in Best Arm Identification for Combinatorial Semi-bandits NIPS 2023
Model-Free Active Exploration in Reinforcement Learning NIPS 2023
Statistical and Computational Trade-off in Multi-Agent Multi-Armed Bandits NIPS 2023
On the Sample Complexity of Representation Learning in Multi-Task Bandits with Global and Local Structure AAAI 2023
Nearly Optimal Latent State Decoding in Block MDPs AISTATS 2023
Best Arm Identification in Multi-Agent Multi-Armed Bandits ICML 2023
Minimal Expected Regret in Linear Quadratic Control AISTATS 2022
Thresholded Lasso Bandit ICML 2022
Adaptive Sampling for Best Policy Identification in Markov Decision Processes ICML 2021
Fast Pure Exploration via Frank-Wolfe NIPS 2021
Navigating to the Best Policy in Markov Decision Processes NIPS 2021
Regret in Online Recommendation Systems NIPS 2020
Optimal Best-arm Identification in Linear Bandits NIPS 2020
Optimal Algorithms for Multiplayer Multi-Armed Bandits AISTATS 2020
Optimal Sampling and Clustering in the Stochastic Block Model NIPS 2019
Exploration in Structured Reinforcement Learning NIPS 2018
Minimal Exploration in Structured Stochastic Bandits NIPS 2017
Collaborative Clustering: Sample Complexity and Efficient Algorithms ALT 2017
Optimal Cluster Recovery in the Labeled Stochastic Block Model NIPS 2016
Fast and Memory Optimal Low-Rank Matrix Approximation NIPS 2015
Combinatorial Bandits Revisited NIPS 2015
Unimodal Bandits: Regret Lower Bounds and Optimal Algorithms ICML 2014
Lipschitz Bandits: Regret Lower Bound and Optimal Algorithms COLT 2014
Streaming, Memory Limited Algorithms for Community Detection NIPS 2014
Community Detection via Random and Adaptive Sampling COLT 2014
Two-Target Algorithms for Infinite-Armed Bandits with Bernoulli Rewards NIPS 2013