Best-arm identification

Best-Arm Identification in Unimodal Bandits
We study the fixed-confidence best-arm identification problem in unimodal bandits, in which the means of the arms increase with the …
PDF Cite
Solving Pure Exploration Problems with the Top Two Approach
In pure exploration problems for stochastic multi-armed bandits, the objective is to answer inquiries regarding a set of unknown …
PDF Cite Slides Video
Differentially Private Best-Arm Identification
Best Arm Identification (BAI) problems are progressively used for data-sensitive applications, such as designing adaptive clinical …
PDF Cite Code Slides
On the Complexity of Differentially Private Best-Arm Identification with Fixed Confidence
Best Arm Identification (BAI) problems are progressively used for data-sensitive applications, such as designing adaptive clinical …
PDF Cite Code Poster Slides Video
Non-Asymptotic Analysis of a UCB-based Top Two Algorithm
A Top Two sampling rule for bandit identification is a method which selects the next arm to sample from among two candidate arms, a …
PDF Cite Code Poster Slides Video
Dealing with Unknown Variances in Best-Arm Identification
The problem of identifying the best arm among a collection of items having Gaussian rewards distribution is well understood when the …
PDF Cite Slides Video
Top Two Algorithms Revisited
Top Two algorithms arose as an adaptation of Thompson sampling to best arm identification in multi-armed bandit models (Russo, 2016), …
PDF Cite Code Poster Slides Video
Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback
Combinatorial bandits with semi-bandit feedback generalize multi-armed bandits, where the agent chooses sets of arms and observes a …
PDF Cite Slides Video