2 citations · 7 across the 12 of their papers we have counts for
5 papers · 1 filter
Non-Asymptotic Analysis of a UCB-based Top Two Algorithm
Marc Jourdan, Rémy Degenne
A Top Two sampling rule for bandit identification is a method which selects the next arm to sample from among two candidate arms, a leader and a challenger. Due to their simplicity…
Dealing with Unknown Variances in Best-Arm Identification
Marc Jourdan, Rémy Degenne, Emilie Kaufmann
The problem of identifying the best arm among a collection of items having Gaussian rewards distribution is well understood when the variances are known. Despite its practical rele…
Choosing Answers in -Best-Answer Identification for Linear Bandits
Marc Jourdan, Rémy Degenne
In pure-exploration problems, information is gathered sequentially to answer a question on the stochastic environment. While best-arm identification for linear bandits has been ext…
Top Two Algorithms Revisited
Marc Jourdan, Rémy Degenne, Dorian Baudry +2
Top Two algorithms arose as an adaptation of Thompson sampling to best arm identification in multi-armed bandit models (Russo, 2016), for parametric families of arms. They select t…
On Elimination Strategies for Bandit Fixed-Confidence Identification
Andrea Tirinzoni, Rémy Degenne
Elimination algorithms for bandit identification, which prune the plausible correct answers sequentially until only one remains, are computationally convenient since they reduce th…