Search Results for author:
Found 6 papers, 1 papers with code
A/B/n Testing with Control in the Presence of Subpopulations
At every time step, a subpopulation is sampled and an arm is chosen: the resulting observation is an independent draw from the arm conditioned on the subpopulation.
Safe Testing
We develop the theory of hypothesis testing based on the e-value, a notion of evidence that, unlike the p-value, allows for effortlessly combining results from several studies in the common scenario where the decision to perform a new study may depend on previous outcomes.
Mixture Martingales Revisited with Applications to Sequential Tests and Confidence Intervals
This paper presents new deviation inequalities that are valid uniformly in time under adaptive sampling in a multi-armed bandit model.
Sequential Test for the Lowest Mean: From Thompson to Murphy Sampling
We develop refined non-asymptotic lower bounds, which show that optimality mandates very different sampling behavior for a low vs high true minimum.
Monte-Carlo Tree Search by Best Arm Identification
Recent advances in bandit tools and techniques for sequential learning are steadily enabling new applications and are promising the resolution of a range of challenging related problems.
Maximin Action Identification: A New Bandit Framework for Games
We study an original problem of pure exploration in a strategic bandit model motivated by Monte Carlo Tree Search.
