31 citations · 38 across the 4 of their papers we have counts for
6 papers
Tight (Lower) Bounds for the Fixed Budget Best Arm Identification Bandit Problem
Alexandra Carpentier, Andrea Locatelli
We consider the problem of \textit{best arm identification} with a \textit{fixed budget }, in the -armed stochastic bandit setting, with arms distribution defined on .…
An optimal algorithm for the Thresholding Bandit Problem
Andrea Locatelli, Maurilio Gutzeit, Alexandra Carpentier
We study a specific \textit{combinatorial pure exploration stochastic bandit problem} where the learner aims at finding the set of arms whose means are above a given threshold, up…
Upper-Confidence-Bound Algorithms for Active Learning in Multi-Armed Bandits
Alexandra Carpentier, Alessandro Lazaric, Mohammad Ghavamzadeh +3
In this paper, we study the problem of estimating uniformly well the mean values of several distributions given a finite budget of samples. If the variance of the distributions wer…
Simple regret for infinitely many armed bandits
Alexandra Carpentier, Michal Valko
We consider a stochastic bandit problem with infinitely many arms. In this setting, the learner has no chance of trying all the arms even once and has to dedicate its limited numbe…
Toward Optimal Stratification for Stratified Monte-Carlo Integration
Alexandra Carpentier, Remi Munos
We consider the problem of adaptive stratified sampling for Monte Carlo integration of a noisy function, given a finite budget n of noisy evaluations to the function. We tackle in…
Adaptive Stratified Sampling for Monte-Carlo integration of Differentiable functions
Alexandra Carpentier, Rémi Munos
We consider the problem of adaptive stratified sampling for Monte Carlo integration of a differentiable function given a finite number of evaluations to the function. We construct…