Comments on the "Core vector machines: Fast SVM training on very large data sets"

Journal of Machine Learning Research

Volumn 8, Issue , 2007, Pages 291-301

  Loosli, Gaëlle ^a   Canu, Stéphane ^a  

^a University of Rouen   (France)

Author keywords

CVM; KKT gap; Large scale; Stopping condition; Stopping criteria; SVM

Indexed keywords

ALGORITHMS; DATABASE SYSTEMS; VECTORS;

CORE VECTOR MACHINES (CVM); STOPPING CONDITION; STOPPING CRITERIA;

LEARNING SYSTEMS;

EID: 33847169137     PISSN: 15324435     EISSN: 15337928     Source Type: Journal    
DOI: None     Document Type: Article

References (9)

1. Chih-Chung Chang and Chih-Jen Lin. LIBSVM: a library for support vector machines, 2001a. URL http://www.csie.ntu.edu.tw/~cjlin/libsvm.
2. Chih-Chung Chang and Chih-Jen Lin. Training v-support vector classifiers: Theory and algorithms. Neural Computation, (9):2119-2147, 2001b.
3. Pai-Hsuen Chen, Chih-Jen Lin, and Bernhard Schölkopf. A tutorial on v-support vector machines. Applied Stochastic Models in Business and Industry, 21(2):111-136, 2005.
4. Rong-En Fan, Pai-Hsuen Chen, and Chih-Jen Lin. Working set selection using second order information for training support vector machines. Journal of Machine Learning Research, 2005.
5. Gaëlle Loosli. Fast svm toolbox in Matlab based on SimpleSVM algorithm, 2004. http://asi.insa-rouen.fr/~gloosli/simpleSVM.html.
6. John Platt. Fast training of support vector machines using sequential minimal optimization. In B. Scholkopf, C. Burges, and A. Smola, editors, Advanced in Kernel Methods - Support Vector Learning, pages 185-208. MIT Press, 1999.
7. Bernhard Schölkopf and Alexander J. Smola. Learning with Kernels. MIT Press, 2002.
8. Ivor W. Tsang, James T. Kwok, and Pak-Ming Cheung. Core vector machines: Fast SVM training on very large data sets. J. Mach. Learn. Res., 6:363-392, 2005.
9. S. V. N Vishwanathan, Alexander J. Smola, and M. Narasimha Murty. SimpleSVM. Proceedings of the Twentieth International Conference on Machine Learning, 2003.