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19952026
most citedInverse Problem for a Curved Quantum Guide

1k citations

Showing 2017 · math.STShow all

13 papers · 2 filters

math.ST2017★ 9 cited

Thresholding Bandit for Dose-ranging: The Impact of Monotonicity

Aurélien Garivier, Pierre Ménard, Laurent Rossi +1

We analyze the sample complexity of the thresholding bandit problem, with and without the assumption that the mean values of the arms are increasing. In each case, we provide a low…

math.ST2017★ 4 cited

A Central Limit Theorem for Wasserstein type distances between two different laws

Philippe Berthet, Jean-Claude Fort, Thierry Klein

This article is dedicated to the estimation of Wasserstein distances and Wasserstein costs between two distinct continuous distributions and on . The estimator i…

math.ST2017★ 25 cited

Optimal non-asymptotic bound of the Ruppert-Polyak averaging without strong convexity

Sébastien Gadat, Fabien Panloup

This paper is devoted to the non-asymptotic control of the mean-squared error for the Ruppert-Polyak stochastic averaged gradient descent introduced in the seminal contributions of…

math.ST2017★ 3 cited

Sensitivity analysis using perturbed-law based indices for quantiles and application to an industrial case

Roman Sueur, Bertrand Iooss, Thibault Delage

In this paper, we present perturbed law-based sensitivity indices and how to adapt them for quantile-oriented sensitivity analysis. We exhibit a simple way to compute these indices…

math.ST2017★ 6 cited

Properties and comparison of some Kriging sub-model aggregation methods

François Bachoc, Nicolas Durrande, Didier Rullière +1

Kriging is a widely employed technique, in particular for computer experiments, in machine learning or in geostatistics. An important challenge for Kriging is the computational bur…

math.ST2017★ 19 cited

Shapley effects for sensitivity analysis with correlated inputs: comparisons with Sobol' indices, numerical estimation and applications

Bertrand Iooss, Clémentine Prieur

The global sensitivity analysis of a numerical model aims to quantify, by means of sensitivity indices estimate, the contributions of each uncertain input variable to the model out…