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Learning from Data as an Inverse Problem
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SYSNO ASEP 0105196 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title Learning from Data as an Inverse Problem Title Učení na základě dat jako inverzní úloha Author(s) Kůrková, Věra (UIVT-O) RID, SAI, ORCID Source Title COMPSTAT Proceedings in Computational Statistics. - Heidelberg : Physica-Verlag, 2004 / Antoch J. - ISBN 978-3-7908-1554-2 Pages s. 1377-1384 Number of pages 8 s. Publication form CD ROM - CD ROM Action COMPSTAT 2004. Symposium /16./ Event date 23.08.2004-27.08.2004 VEvent location Prague Country CZ - Czech Republic Event type WRD Language eng - English Country DE - Germany Keywords learning from data ; generalization ; minimization of empirical error ; regularization ; kernel methods Subject RIV BA - General Mathematics R&D Projects GA201/02/0428 GA ČR - Czech Science Foundation (CSF) CEZ AV0Z1030915 - UIVT-O Annotation We reformulate the problem of minimization of an empirical error functional as a linear inverse problem by introducing an operator defined in terms of evaluations at the input data. Workplace Institute of Computer Science Contact Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Year of Publishing 2005
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