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Using the Nonsmooth Analysis in a Learning Process

SYSNO ASEP	0355020
Document Type	C - Proceedings Paper (int. conf.)
R&D Document Type	Conference Paper
Title	Using the Nonsmooth Analysis in a Learning Process
Author(s)	Jiřina, Marcel (UIVT-O)_{SAI, RID} Jiřina jr., M. (CZ)
Source Title	Proceeding of The 2010 IRAST International Congress on Computer Applications and Computational Science. - - : IRAST, 2010 / Chellappan S. ; Cheng A.C. ; Min M. ; Quang V.N ; Ramalingam P. ; Yang H. - ISBN 978-981-08-6846-8
Pages	s. 91-94
Number of pages	4 s.
Publication form	CD ROM - CD ROM
Action	CACS 2010. 2010 IRAST International Congress on Computer Applications and Computational Science
Event date	04.12.2010--06.12.2010
VEvent location	Singapore
Country	SG - Singapore
Event type	WRD
Language	eng - English
Country	US - United States
Keywords	nonsmooth analysis ; pattern classification ; multivariate systems ; 1-NN classifier ; weighted distances
Subject RIV	BB - Applied Statistics, Operational Research
R&D Projects	1M0567 GA MŠMT - Ministry of Education, Youth and Sports (MEYS)
CEZ	AV0Z10300504 - UIVT-O (2005-2011)
Annotation	We propose an unconventional updating algorithm for weighting features for a classification task with abrupt changes of the error function. Using a so-called nonsmooth analysis we prove the quadratic convergence of such a learning process. For the dynamic optimization of the step size we use approach similar to Runge’s method of a half step. Finally we demonstrate its classification abilities on artificial as well as on real-life classification tasks.
Workplace	Institute of Computer Science
Contact	Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800
Year of Publishing	2011

Number of the records: 1