Document Detail


Asymptotic convergence of an SMO algorithm without any assumptions.
MedLine Citation:
PMID:  18244425     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
The asymptotic convergence of C.-J. Lin (2001) can be applied to a modified SMO (sequential minimal optimization) algorithm by S.S. Keerthi et al. (2001) with some assumptions. The author shows that for this algorithm those assumptions are not necessary.
Authors:
Chih-Jen Lin
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  IEEE transactions on neural networks / a publication of the IEEE Neural Networks Council     Volume:  13     ISSN:  1045-9227     ISO Abbreviation:  IEEE Trans Neural Netw     Publication Date:  2002  
Date Detail:
Created Date:  2008-02-04     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101211035     Medline TA:  IEEE Trans Neural Netw     Country:  United States    
Other Details:
Languages:  eng     Pagination:  248-50     Citation Subset:  -    
Affiliation:
Dept. of Comput. Sci. and Inf. Eng., Nat. Taiwan Univ., Taipei.
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