A new approach for finding an optimal solution and regularization by learning dynamic momentum

Eun Mi Kim, Jong Cheol Jeong, Bae Ho Lee

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Regularization and finding optimal solution for the classification problems are well known issue in the machine learning, but most of researches have been separately studied or considered as a same problem about these two issues. However, it is obvious that these approaches are not always possible because the evaluation of the performance in classification problems is mostly based on the data distribution and learning methods; therefore this paper suggests a new approach to simultaneously deal with finding optimal regularization parameter and solution in classification and regression problems by introducing dynamically rescheduled momentum with modified SVM in kernel space.

Original languageEnglish
Title of host publicationArtificial Intelligence and Soft Computing - ICAISC 2006 - 8th International Conference, Proceedings
Pages29-36
Number of pages8
DOIs
StatePublished - 2006
Event8th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2006 - Zakopane, Poland
Duration: Jun 25 2006Jun 29 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4029 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2006
Country/TerritoryPoland
CityZakopane
Period6/25/066/29/06

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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