← Authors

Alexandra Carpentier

33 papers · 2011–2025 · 6 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (14) πŸ—ΊοΈ Taxonomy Completionist (20) 🐝 Cross-Pollinator (12) 🌈 Renaissance Researcher (5) 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (6) 🧭 Keyword Pioneer πŸ”¬ Deep Specialist (12) πŸ† Keyword Champion (2) 🌱 Topic Pioneer πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (66) πŸ’Ž Century Club (33) πŸ”₯ Unstoppable (15) ⚑ Prolific Year (5)

Conferences

ICML (10) NIPS (9) AISTATS (6) COLT (4) ALT (3) JMLR (1)

Top co-authors

Michal Valko (8) RΓ©mi Munos (8) Andrea Locatelli (6) James Cheshire (3) Nicolas Verzelen (3) Pierre Menard (3) El Mehdi Saad (2) Claire Vernade (2) Maurilio Gutzeit (2) Odalric-ambrym Maillard (2)

Research topics

Statistics (2)

Keywords

multi-armed bandit (13) regret bound (11) online learning (6) stochastic optimization (5) minimax optimal (4) stratified sampling (4) active learning (4) upper confidence bound (4) stochastic bandit (3) linear bandit (3) bandit algorithm (3) cumulative regret (3) monte carlo integration (3) online algorithm (3) thresholding bandit (3) variance reduction (3) regret minimization (2) compressed sensing (2) minimax regret (2) minimax optimization (2)

Papers

Clustering with bandit feedback: breaking down the computation/information gap ALT 2025
On Weak Regret Analysis for Dueling Bandits NIPS 2024
Online Learning with Feedback Graphs: The True Shape of Regret ICML 2023
Active Ranking of Experts Based on their Performances in Many Tasks ICML 2023
The price of unfairness in linear bandits with biased feedback NIPS 2022
Problem Dependent View on Structured Thresholding Bandit Problems ICML 2021
Bandits with many optimal arms NIPS 2021
The Influence of Shape Constraints on the Thresholding Bandit Problem COLT 2020
Linear bandits with Stochastic Delayed Feedback ICML 2020
Stochastic bandits with arm-dependent delays ICML 2020
Active multiple matrix completion with adaptive confidence sets AISTATS 2019
A minimax near-optimal algorithm for adaptive rejection sampling ALT 2019
Rotting bandits are no harder than stochastic ones AISTATS 2019
Adaptivity to Smoothness in X-armed bandits COLT 2018
An Adaptive Strategy for Active Learning with Smooth Decision Boundary ALT 2018
Two-Sample Tests for Large Random Graphs Using Network Statistics COLT 2017
Pliable Rejection Sampling ICML 2016
Revealing Graph Bandits for Maximizing Local Influence AISTATS 2016
An optimal algorithm for the Thresholding Bandit Problem ICML 2016
Tight (Lower) Bounds for the Fixed Budget Best Arm Identification Bandit Problem COLT 2016
Learning Relationships between Data Obtained Independently AISTATS 2016
Adaptive Strategy for Stratified Monte Carlo Sampling JMLR 2015
Implementable confidence sets in high dimensional regression AISTATS 2015
Simple regret for infinitely many armed bandits ICML 2015
Extreme bandits NIPS 2014
Toward Optimal Stratification for Stratified Monte-Carlo Integration ICML 2013
Stochastic Simultaneous Optimistic Optimization ICML 2013
Adaptive Stratified Sampling for Monte-Carlo integration of Differentiable functions NIPS 2012
Online allocation and homogeneous partitioning for piecewise constant mean-approximation NIPS 2012
Bandit Theory meets Compressed Sensing for high dimensional Stochastic Linear Bandit AISTATS 2012
Bandit Algorithms boost Brain Computer Interfaces for motor-task selection of a brain-controlled button NIPS 2012
Finite Time Analysis of Stratified Sampling for Monte Carlo NIPS 2011
Sparse Recovery with Brownian Sensing NIPS 2011