activity
20162022
most citedAn optimal algorithm for the Thresholding Bandit Problem

64 citations · 131 across the 6 of their papers we have counts for

collaborators

6 papers

stat.ME2022★ 6 cited

Modelling volume-outcome relationships in health care

Maurilio Gutzeit, Johannes Rauh, Maximilian Kähler +1

Despite the ongoing strong interest in associations between quality of care and the volume of health care providers, a unified statistical framework for analyzing them is missing,…

math.ST2019

Minimax -Separation Rate in Testing the Sobolev-Type Regularity of a function

Maurilio Gutzeit

In this paper we study the problem of testing if an function belonging to a certain -Sobolev-ball of radius with smoothness level indeed exhibit…

stat.ME2017★ 32 cited

Two-sample Hypothesis Testing for Inhomogeneous Random Graphs

Debarghya Ghoshdastidar, Maurilio Gutzeit, Alexandra Carpentier +1

The study of networks leads to a wide range of high dimensional inference problems. In many practical applications, one needs to draw inference from one or few large sparse network…

stat.ME2017★ 28 cited

Two-Sample Tests for Large Random Graphs Using Network Statistics

Debarghya Ghoshdastidar, Maurilio Gutzeit, Alexandra Carpentier +1

We consider a two-sample hypothesis testing problem, where the distributions are defined on the space of undirected graphs, and one has access to only one observation from each mod…

math.ST2017★ 1 cited

Minimax Euclidean Separation Rates for Testing Convex Hypotheses in

Gilles Blanchard, Alexandra Carpentier, Maurilio Gutzeit

We consider composite-composite testing problems for the expectation in the Gaussian sequence model where the null hypothesis corresponds to a convex subset of $\math…

stat.ML2016★ 64 cited

An optimal algorithm for the Thresholding Bandit Problem

Andrea Locatelli, Maurilio Gutzeit, Alexandra Carpentier

We study a specific \textit{combinatorial pure exploration stochastic bandit problem} where the learner aims at finding the set of arms whose means are above a given threshold, up…