The power of random information for numerical approximation and integration

Autor:	Sonnleitner, Mathias
Rok vydání:	2022
Předmět:	Mathematics - Numerical Analysis Mathematics - Probability 11K38 41A25 41A63 52A23 52A39 60G15 62C05 65D15 65D30 65Y20
Druh dokumentu:	Working Paper
Popis:	This thesis investigates the quality of randomly collected data by employing a framework built on information-based complexity, a field related to the numerical analysis of abstract problems. The quality or power of gathered information is measured by its radius which is the uniform error obtainable by the best possible algorithm using it. The main aim is to present progress towards understanding the power of random information for approximation and integration problems. Comment: Phd thesis, University of Passau (2022), 165 pages. Based on arXiv:1907.06435, arXiv:2009.11275, arXiv:2010.04522, arXiv:2109.14504
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2209.07266 Zobrazit plný text záznamu View this record from Arxiv