Sequential minimal optimization: Difference between revisions

Revision as of 15:32, 13 March 2013

Revision as of 16:20, 19 July 2013

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| title = Sequential Minimal Optimization: A Fast Algorithm for Training Support Vector Machines

| id = {{citeseerx|10.1.1.43.4376}}

}}</ref> SMO is widely used for training support vector machines and is implemented by the popular libsvm[[LIBSVM]] tool.<ref>{{cite journal
|last1=Chang |first1=Chih-Chung
|last2=Lin Chang and |first2=Chih-Jen
|title=LIBSVM: LinA (2001).library ''[http://www.csie.ntu.edu.tw/~cjlin/papers/libsvm.pdffor LIBSVM:support avector Librarymachines
|journal=ACM forTransactions Supporton VectorIntelligent Machines]''.Systems and Technology
|volume=2 |issue=3 |year=2011
}}</ref><ref>Luca Zanni (2006). ''[http://jmlr.csail.mit.edu/papers/volume7/zanni06a/zanni06a.pdf Parallel Software for Training Large Scale Support Vector Machines on Multiprocessor Systems]''.</ref> The publication of the SMO algorithm in 1998 has generated a lot of excitement in the SVM community, as previously available methods for SVM training were much more complex and required expensive third-party [[Quadratic programming|QP]] solvers.<ref>{{Citation

| last = Rifkin | first = Ryan

| year = 2002