31 citations · 85 across the 11 of their papers we have counts for
13 papers · 1 filter
Problem Dependent View on Structured Thresholding Bandit Problems
James Cheshire, Pierre Ménard, Alexandra Carpentier
We investigate the problem dependent regime in the stochastic Thresholding Bandit problem (TBP) under several shape constraints. In the TBP, the objective of the learner is to outp…
Generalized non-stationary bandits
Anne Gael Manegueu, Alexandra Carpentier, Yi Yu
In this paper, we study a non-stationary stochastic bandit problem, which generalizes the switching bandit problem. On top of the switching bandit problem (\textbf{Case a}), we are…
The Elliptical Potential Lemma Revisited
Alexandra Carpentier, Claire Vernade, Yasin Abbasi-Yadkori
This note proposes a new proof and new perspectives on the so-called Elliptical Potential Lemma. This result is important in online learning, especially for linear stochastic bandi…
Stochastic bandits with arm-dependent delays
Anne Gael Manegueu, Claire Vernade, Alexandra Carpentier +1
Significant work has been recently dedicated to the stochastic delayed bandit setting because of its relevance in applications. The applicability of existing algorithms is however…
Restless dependent bandits with fading memory
Oleksandr Zadorozhnyi, Gilles Blanchard, Alexandra Carpentier
We study the stochastic multi-armed bandit problem in the case when the arm samples are dependent over time and generated from so-called weak $\cC$-mixing processes. We establish a…
A minimax near-optimal algorithm for adaptive rejection sampling
Juliette Achdou, Joseph C. Lam, Alexandra Carpentier +1
Rejection Sampling is a fundamental Monte-Carlo method. It is used to sample from distributions admitting a probability density function which can be evaluated exactly at any given…