Alexandra Carpentier

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 41

Top Topics

Shape Constraints

Stochastic Systems

Bandit Problems

Top Venues

Publications

Emmanuel Pilliat, Alexandra Carpentier, Nicolas Verzelen
Optimal rates for ranking a permuted isotonic matrix in polynomial time. SODA (2024)
Victor Thuot, Alexandra Carpentier, Christophe Giraud, Nicolas Verzelen
Active clustering with bandit feedback. CoRR (2024)
Alexandra Carpentier
A simple and improved algorithm for noisy, convex, zeroth-order optimisation. CoRR (2024)
El Mehdi Saad, Nicolas Verzelen, Alexandra Carpentier
Active Ranking of Experts Based on their Performances in Many Tasks. CoRR (2023)
Tomás Kocák, Alexandra Carpentier
Online Learning with Feedback Graphs: The True Shape of Regret. CoRR (2023)
Tomás Kocák, Alexandra Carpentier
Online Learning with Feedback Graphs: The True Shape of Regret. ICML (2023)
El Mehdi Saad, Nicolas Verzelen, Alexandra Carpentier
Active Ranking of Experts Based on their Performances in Many Tasks. ICML (2023)
Solenne Gaucher, Alexandra Carpentier, Christophe Giraud
The price of unfairness in linear bandits with biased feedback. NeurIPS (2022)
Anne Gael Manegueu, Alexandra Carpentier, Yi Yu
Generalized non-stationary bandits. CoRR (2021)
Rianne de Heide, James Cheshire, Pierre Ménard, Alexandra Carpentier
Bandits with many optimal arms. CoRR (2021)
James Cheshire, Pierre Ménard, Alexandra Carpentier
Problem Dependent View on Structured Thresholding Bandit Problems. CoRR (2021)
Rianne de Heide, James Cheshire, Pierre Ménard, Alexandra Carpentier
Bandits with many optimal arms. NeurIPS (2021)
James Cheshire, Pierre Ménard, Alexandra Carpentier
Problem Dependent View on Structured Thresholding Bandit Problems. ICML (2021)
Julien Chhor, Alexandra Carpentier
Goodness-of-Fit Testing for Hölder-Continuous Densities: Sharp Local Minimax Rates. CoRR (2021)
Alexandra Carpentier, Claire Vernade, Yasin Abbasi-Yadkori
The Elliptical Potential Lemma Revisited. CoRR (2020)
James Cheshire, Pierre Ménard, Alexandra Carpentier
The Influence of Shape Constraints on the Thresholding Bandit Problem. COLT (2020)
Claire Vernade, Alexandra Carpentier, Tor Lattimore, Giovanni Zappella, Beyza Ermis, Michael Brückner
Linear bandits with Stochastic Delayed Feedback. ICML (2020)
James Cheshire, Pierre Ménard, Alexandra Carpentier
The Influence of Shape Constraints on the Thresholding Bandit Problem. CoRR (2020)
Anne Gael Manegueu, Claire Vernade, Alexandra Carpentier, Michal Valko
Stochastic bandits with arm-dependent delays. ICML (2020)
Anne Gael Manegueu, Claire Vernade, Alexandra Carpentier, Michal Valko
Stochastic bandits with arm-dependent delays. CoRR (2020)
Juliette Achdou, Joseph Lam-Weil, Alexandra Carpentier, Gilles Blanchard
A minimax near-optimal algorithm for adaptive rejection sampling. ALT (2019)
Alexandra Carpentier, Olivier Collier, Laëtitia Comminges, Alexandre B. Tsybakov, Yuhao Wang
Minimax Rate of Testing in Sparse Linear Regression. Autom. Remote. Control. 80 (10) (2019)
Oleksandr Zadorozhnyi, Gilles Blanchard, Alexandra Carpentier
Restless dependent bandits with fading memory. CoRR (2019)
Andrea Locatelli, Alexandra Carpentier, Michal Valko
Active multiple matrix completion with adaptive confidence sets. AISTATS (2019)
Julien Seznec, Andrea Locatelli, Alexandra Carpentier, Alessandro Lazaric, Michal Valko
Rotting bandits are no harder than stochastic ones. AISTATS (2019)
Joseph Lam-Weil, Alexandra Carpentier, Bharath K. Sriperumbudur
Local minimax rates for closeness testing of discrete distributions. CoRR (2019)
Julien Seznec, Andrea Locatelli, Alexandra Carpentier, Alessandro Lazaric, Michal Valko
Rotting bandits are no harder than stochastic ones. CoRR (2018)
Andrea Locatelli, Alexandra Carpentier
Adaptivity to Smoothness in X-armed bandits. COLT (2018)
Claire Vernade, Alexandra Carpentier, Giovanni Zappella, Beyza Ermis, Michael Brückner
Contextual Bandits under Delayed Feedback. CoRR (2018)
Andrea Locatelli, Alexandra Carpentier, Samory Kpotufe
An Adaptive Strategy for Active Learning with Smooth Decision Boundary. ALT (2018)
Juliette Achdou, Joseph C. Lam, Alexandra Carpentier, Gilles Blanchard
A minimax near-optimal algorithm for adaptive rejection sampling. CoRR (2018)
Debarghya Ghoshdastidar, Maurilio Gutzeit, Alexandra Carpentier, Ulrike von Luxburg
Two-Sample Tests for Large Random Graphs Using Network Statistics. COLT (2017)
Andrea Locatelli, Alexandra Carpentier, Samory Kpotufe
An Adaptive Strategy for Active Learning with Smooth Decision Boundary. CoRR (2017)
Andrea Locatelli, Alexandra Carpentier, Samory Kpotufe
Adaptivity to Noise Parameters in Nonparametric Active Learning. COLT (2017)
Alexandra Carpentier, Andrea Locatelli
Tight (Lower) Bounds for the Fixed Budget Best Arm Identification Bandit Problem. COLT (2016)
Alexandra Carpentier, Michal Valko
Revealing Graph Bandits for Maximizing Local Influence. AISTATS (2016)
Alexandra Carpentier, Teresa Schlueter
Learning Relationships between Data Obtained Independently. AISTATS (2016)
Andrea Locatelli, Maurilio Gutzeit, Alexandra Carpentier
An optimal algorithm for the Thresholding Bandit Problem. ICML (2016)
Akram Erraqabi, Michal Valko, Alexandra Carpentier, Odalric-Ambrym Maillard
Pliable Rejection Sampling. ICML (2016)
Alexandra Carpentier, Andrea Locatelli
Tight (Lower) Bounds for the Fixed Budget Best Arm Identification Bandit Problem. CoRR (2016)
Andrea Locatelli, Maurilio Gutzeit, Alexandra Carpentier
An optimal algorithm for the Thresholding Bandit Problem. CoRR (2016)
Alexandra Carpentier
Implementable confidence sets in high dimensional regression. AISTATS (2015)
Alexandra Carpentier, Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos, Peter Auer, András Antos
Upper-Confidence-Bound Algorithms for Active Learning in Multi-Armed Bandits. CoRR (2015)
Alexandra Carpentier, Michal Valko
Simple regret for infinitely many armed bandits. ICML (2015)
Alexandra Carpentier, Rémi Munos, András Antos
Adaptive strategy for stratified Monte Carlo sampling. J. Mach. Learn. Res. 16 (2015)
Alexandra Carpentier, Michal Valko
Simple regret for infinitely many armed bandits. CoRR (2015)
Alexandra Carpentier, Rémi Munos
Minimax number of strata for online stratified sampling: The case of noisy samples. Theor. Comput. Sci. 558 (2014)
Alexandra Carpentier, Michal Valko
Extreme bandits. NIPS (2014)
Michal Valko, Alexandra Carpentier, Rémi Munos
Stochastic Simultaneous Optimistic Optimization. ICML (2) (2013)
Alexandra Carpentier, Rémi Munos
Toward Optimal Stratification for Stratified Monte-Carlo Integration. ICML (2) (2013)
Joan Fruitet, Alexandra Carpentier, Rémi Munos, Maureen Clerc
Bandit Algorithms boost Brain Computer Interfaces for motor-task selection of a brain-controlled button. NIPS (2012)
Alexandra Carpentier, Rémi Munos
Minimax Number of Strata for Online Stratified Sampling Given Noisy Samples. ALT (2012)
Alexandra Carpentier, Rémi Munos
Adaptive Stratified Sampling for Monte-Carlo integration of Differentiable functions. NIPS (2012)
Alexandra Carpentier, Rémi Munos
Bandit Theory meets Compressed Sensing for high dimensional Stochastic Linear Bandit. AISTATS (2012)
Alexandra Carpentier, Odalric-Ambrym Maillard
Online allocation and homogeneous partitioning for piecewise constant mean-approximation. NIPS (2012)
Alexandra Carpentier, Rémi Munos
Finite Time Analysis of Stratified Sampling for Monte Carlo. NIPS (2011)
Alexandra Carpentier, Alessandro Lazaric, Mohammad Ghavamzadeh, Rémi Munos, Peter Auer
Upper-Confidence-Bound Algorithms for Active Learning in Multi-armed Bandits. ALT (2011)
Alexandra Carpentier, Odalric-Ambrym Maillard, Rémi Munos
Sparse Recovery with Brownian Sensing. NIPS (2011)