Minimax Number of Strata for Online Stratified Sampling Given Noisy Samples

DOI10.1007/978-3-642-34106-9_20zbMath1416.62070arXiv1205.4095OpenAlexW1564051403MaRDI QIDQ3164823

Rémi Munos, Alexandra Carpentier

Publication date: 16 October 2012

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1205.4095

zbMATH Keywords

online learningMonte Carlo integrationstratified samplingregret boundsbandit theory

Mathematics Subject Classification ID

Sampling theory, sample surveys (62D05) Minimax procedures in statistical decision theory (62C20) Monte Carlo methods (65C05)

Related Items (3)

A one-bit, comparison-based gradient estimator ⋮ Minimax number of strata for online stratified sampling: the case of noisy samples ⋮ Adaptive stratified Monte Carlo algorithm for numerical computation of integrals

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