Alexandre Proutiere
33 papers · 2013–2025 · 6 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (6) π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (13) π§ Keyword Pioneer π Academic Marathon (12)
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Keyword Pioneer
π
Interdisciplinary Bridge
π
Conference Polyglot
(6)
π
Keyword Champion
(2)
ποΈ
Keyword Collector
(112)
π
Conference Pioneer
π
Century Club
(33)
π₯
Unstoppable
(13)
π
Trend Setter
β‘
Prolific Year
(8)
Conferences
NIPS (18)
ICML (8)
AISTATS (3)
COLT (2)
AAAI (1)
ALT (1)
Top co-authors
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