38 citations · 70 across the 19 of their papers we have counts for
5 papers · 1 filter
Deep anytime-valid hypothesis testing
Teodora Pandeva, Patrick Forré, Aaditya Ramdas +1
We propose a general framework for constructing powerful, sequential hypothesis tests for a large class of nonparametric testing problems. The null hypothesis for these problems is…
Active Model Estimation in Markov Decision Processes
Jean Tarbouriech, Shubhanshu Shekhar, Matteo Pirotta +2
We study the problem of efficient exploration in order to learn an accurate model of an environment, modeled as a Markov decision process (MDP). Efficient exploration in this probl…
Adaptive Sampling for Estimating Multiple Probability Distributions
Shubhanshu Shekhar, Tara Javidi, Mohammad Ghavamzadeh
We consider the problem of allocating samples to a finite set of discrete distributions in order to learn them uniformly well in terms of four common distance measures: ,…
Multiscale Gaussian Process Level Set Estimation
Shubhanshu Shekhar, Tara Javidi
In this paper, the problem of estimating the level set of a black-box function from noisy and expensive evaluation queries is considered. A new algorithm for this problem in the Ba…
Gaussian Process bandits with adaptive discretization
Shubhanshu Shekhar, Tara Javidi
In this paper, the problem of maximizing a black-box function is studied in the Bayesian framework with a Gaussian Process (GP) prior. In particular,…