An efficient SMO-like algorithm for multiclass SVM

Neural Networks for Signal Processing - Proceedings of the IEEE Workshop

Volumn 2002-January, Issue , 2002, Pages 297-306

  Aiolli, F ^a   Sperduti, A ^b  

^a UNIVERSITY OF PISA   (Italy)

^b UNIVERSITY OF PADOVA   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE; LEARNING SYSTEMS; OPTIMIZATION;

FAST OPTIMIZATIONS; KERNEL MACHINE; LAGRANGIAN; MACHINE LEARNING RESEARCH; MULTICLASS SVM; PATTERN SELECTION; SEQUENTIAL MINIMAL OPTIMIZATION;

SIGNAL PROCESSING;

EID: 84868254493     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/NNSP.2002.1030041     Document Type: Conference Paper

References (6)

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2. K. Crammer and Y. Singer, "On the Algorithmic Implementation of Multiclass Kernel-based Machines," Journal of Machine Learning Research, vol. 2(Dec), pp. 265-292, 2001.
3. T. G. Dietterich and G. Bakiri, "Solving multiclass learning problems via error correcting output codes," Journal of Artificial Intelligence Research, vol. 2, pp. 263-286, 1995.
4. J. Platt, "Fast training of Support Vector Machines using sequential minimal optimization," Advances in Kernel Methods - Support Vector Learning, 1998.
5. R. E. Schapire and Y. Singer, "Improved boosting algorithms using confidence-rated predictions," Machine Learning, vol. 37, no. 3, pp. 1-40, 1999.
6. V. Vapnik, Statistical Learning Theory, Wiley, 1998.