Alexandra Carpentier

research

∙ 06/28/2023

Moment inequalities for sums of weakly dependent random fields

We derive both Azuma-Hoeffding and Burkholder-type inequalities for part...

0 Gilles Blanchard, et al. ∙

research

∙ 06/05/2023

Online Learning with Feedback Graphs: The True Shape of Regret

Sequential learning with feedback graphs is a natural extension of the m...

0 Tomáš Kocák, et al. ∙

research

∙ 06/05/2023

Active Ranking of Experts Based on their Performances in Many Tasks

We consider the problem of ranking n experts based on their performances...

0 El Mehdi Saad, et al. ∙

research

∙ 11/08/2022

Optimal Permutation Estimation in Crowd-Sourcing problems

Motivated by crowd-sourcing applications, we consider a model where we h...

0 Pilliat Emmanuel, et al. ∙

research

∙ 03/18/2022

The price of unfairness in linear bandits with biased feedback

Artificial intelligence is increasingly used in a wide range of decision...

0 Solenne Gaucher, et al. ∙

research

∙ 09/09/2021

Goodness-of-Fit Testing for Hölder-Continuous Densities: Sharp Local Minimax Rates

We consider the goodness-of fit testing problem for Hölder smooth densit...

0 Julien Chhor, et al. ∙

research

∙ 06/18/2021

Problem Dependent View on Structured Thresholding Bandit Problems

We investigate the problem dependent regime in the stochastic Thresholdi...

0 James Cheshire, et al. ∙

research

∙ 03/23/2021

Bandits with many optimal arms

We consider a stochastic bandit problem with a possibly infinite number ...

0 Rianne de Heide, et al. ∙

research

∙ 02/01/2021

Generalized non-stationary bandits

In this paper, we study a non-stationary stochastic bandit problem, whic...

0 Anne Gael Manegueu, et al. ∙

research

∙ 11/16/2020

Optimal multiple change-point detection for high-dimensional data

This manuscript makes two contributions to the field of change-point det...

0 Emmanuel Pilliat, et al. ∙

research

∙ 10/26/2020

Estimation of the l_2-norm and testing in sparse linear regression with unknown variance

We consider the related problems of estimating the l_2-norm and the squa...

0 Alexandra Carpentier, et al. ∙

research

∙ 10/20/2020

The Elliptical Potential Lemma Revisited

This note proposes a new proof and new perspectives on the so-called Ell...

0 Alexandra Carpentier, et al. ∙

research

∙ 06/18/2020

Stochastic bandits with arm-dependent delays

Significant work has been recently dedicated to the stochastic delayed b...

0 Anne Gael Manegueu, et al. ∙

research

∙ 06/17/2020

The Influence of Shape Constraints on the Thresholding Bandit Problem

We investigate the stochastic Thresholding Bandit problem (TBP) under se...

0 James Cheshire, et al. ∙

research

∙ 06/25/2019

Restless dependent bandits with fading memory

We study the stochastic multi-armed bandit problem in the case when the ...

0 Oleksandr Zadorozhnyi, et al. ∙

research

∙ 02/01/2019

Local minimax rates for closeness testing of discrete distributions

We consider the closeness testing (or two-sample testing) problem in the...

0 Joseph Lam-Weil, et al. ∙

research

∙ 01/25/2019

Optimal Sparsity Testing in Linear regression Model

We consider the problem of sparsity testing in the high-dimensional line...

0 Alexandra Carpentier, et al. ∙

research

∙ 11/27/2018

Rotting bandits are no harder than stochastic ones

In bandits, arms' distributions are stationary. This is often violated i...

0 Julien Seznec, et al. ∙

research

∙ 10/22/2018

A minimax near-optimal algorithm for adaptive rejection sampling

Rejection Sampling is a fundamental Monte-Carlo method. It is used to sa...

0 Juliette Achdou, et al. ∙

research

∙ 10/06/2018

Total variation distance for discretely observed Lévy processes: a Gaussian approximation of the small jumps

It is common practice to treat small jumps of Lévy processes as Wiener n...

0 Alexandra Carpentier, et al. ∙

research

∙ 09/21/2018

Estimating minimum effect with outlier selection

We introduce one-sided versions of Huber's contamination model, in which...

0 Alexandra Carpentier, et al. ∙

research

∙ 07/05/2018

Contextual Bandits under Delayed Feedback

Delayed feedback is an ubiquitous problem in many industrial systems emp...

0 Claire Vernade, et al. ∙

research

∙ 04/17/2018

Minimax rate of testing in sparse linear regression

We consider the problem of testing the hypothesis that the parameter of ...

0 Alexandra Carpentier, et al. ∙

research

∙ 11/25/2017

An Adaptive Strategy for Active Learning with Smooth Decision Boundary

We present the first adaptive strategy for active learning in the settin...

0 Andrea Locatelli, et al. ∙

research

∙ 07/04/2017

Two-sample Hypothesis Testing for Inhomogeneous Random Graphs

The study of networks leads to a wide range of high dimensional inferenc...

0 Debarghya Ghoshdastidar, et al. ∙

research

∙ 05/17/2017

Two-Sample Tests for Large Random Graphs Using Network Statistics

We consider a two-sample hypothesis testing problem, where the distribut...

0 Debarghya Ghoshdastidar, et al. ∙

research

∙ 03/16/2017

Adaptivity to Noise Parameters in Nonparametric Active Learning

This work addresses various open questions in the theory of active learn...

0 Andrea Locatelli, et al. ∙

research

∙ 05/29/2016

Tight (Lower) Bounds for the Fixed Budget Best Arm Identification Bandit Problem

We consider the problem of best arm identification with a fixed budget T...

0 Alexandra Carpentier, et al. ∙

research

∙ 05/27/2016

An optimal algorithm for the Thresholding Bandit Problem

We study a specific combinatorial pure exploration stochastic bandit pro...

0 Andrea Locatelli, et al. ∙

research

∙ 01/04/2016

Learning relationships between data obtained independently

The aim of this paper is to provide a new method for learning the relati...

0 Alexandra Carpentier, et al. ∙

research

∙ 05/18/2015

Simple regret for infinitely many armed bandits

We consider a stochastic bandit problem with infinitely many arms. In th...

0 Alexandra Carpentier, et al. ∙

research

∙ 01/19/2015

Implementable confidence sets in high dimensional regression

We consider the setting of linear regression in high dimension. We focus...

0 Alexandra Carpentier, et al. ∙

research

∙ 03/12/2013

Toward Optimal Stratification for Stratified Monte-Carlo Integration

We consider the problem of adaptive stratified sampling for Monte Carlo ...

0 Alexandra Carpentier, et al. ∙

research

∙ 10/19/2012

Adaptive Stratified Sampling for Monte-Carlo integration of Differentiable functions

We consider the problem of adaptive stratified sampling for Monte Carlo ...

0 Alexandra Carpentier, et al. ∙

Alexandra Carpentier

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