Training Support Vector Machines via SMO-Type Decomposition Methods - researchr publication related

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Pai-Hsuen Chen, Rong-En Fan, Chih-Jen Lin. Training Support Vector Machines via SMO-Type Decomposition Methods. In Sanjay Jain, Hans-Ulrich Simon, Etsuji Tomita, editors, Algorithmic Learning Theory, 16th International Conference, ALT 2005, Singapore, October 8-11, 2005, Proceedings. Volume 3734 of Lecture Notes in Computer Science, pages 45-62, Springer, 2005. [doi]

The following publications are possibly variants of this publication:

Training Support Vector Machines via SMO-Type Decomposition MethodsPai-Hsuen Chen, Rong-En Fan, Chih-Jen Lin. dis 2005: 15 [doi]

A study on SMO-type decomposition methods for support vector machinesPai-Hsuen Chen, Rong-En Fan, Chih-Jen Lin. tnn, 17(4):893-908, 2006. [doi]

Errata to "On the convergence of the decomposition method for support vector machines"Chih-Jen Lin. tnn, 13(4):1025, 2002. [doi]

On the convergence of the decomposition method for support vector machinesChih-Jen Lin. tnn, 12(6):1288-1298, 2001. [doi]

The analysis of decomposition methods for support vector machinesChih-Chung Chang, Chih-Wei Hsu, Chih-Jen Lin. tnn, 11(4):1003-1008, 2000. [doi]

A Simple Decomposition Method for Support Vector MachinesChih-Wei Hsu, Chih-Jen Lin. ml, 46(1-3):291-314, 2002.

Decomposition methods for linear support vector machinesKai-Min Chung, Wei-Chun Kao, Tony Sun, Chih-Jen Lin. icassp 2003: 868-871 [doi]

Decomposition Methods for Linear Support Vector MachinesWei-Chun Kao, Kai-Min Chung, Chia-Liang Sun, Chih-Jen Lin. neco, 16(8):1689-1704, 2004. [doi]

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