Sequential minimal optimization: Difference between revisions

Revision as of 09:11, 13 December 2011

Revision as of 19:44, 1 September 2012

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| year = 1998

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

| urlid = http://{{citeseerx.ist.psu.edu/viewdoc/download?doi=|10.1.1.43.4376&rep=rep1&type=pdf}}

}}</ref> SMO is widely used for training support vector machines and is implemented by the popular libsvm tool.<ref>Chih-Chung Chang and Chih-Jen Lin (2001). ''[http://www.csie.ntu.edu.tw/~cjlin/papers/libsvm.pdf LIBSVM: a Library for Support Vector Machines]''.</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