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Training a Support Vector Machine in the Primal

2006

Technical Report

ei


Most literature on Support Vector Machines (SVMs) concentrate on the dual optimization problem. In this paper, we would like to point out that the primal problem can also be solved efficiently, both for linear and non-linear SVMs, and there is no reason for ignoring it. Moreover, from the primal point of view, new families of algorithms for large scale SVM training can be investigated.

Author(s): Chapelle, O.
Number (issue): 147
Year: 2006
Month: April
Day: 0

Department(s): Empirical Inference
Bibtex Type: Technical Report (techreport)

Institution: Max Planck Institute for Biological Cybernetics, Tübingen

Digital: 0
Language: en
Note: The version in the "Large Scale Kernel Machines" book is more up to date.
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

Links: PDF

BibTex

@techreport{3597,
  title = {Training a Support Vector Machine in the Primal},
  author = {Chapelle, O.},
  number = {147},
  organization = {Max-Planck-Gesellschaft},
  institution = {Max Planck Institute for Biological Cybernetics, Tübingen},
  school = {Biologische Kybernetik},
  month = apr,
  year = {2006},
  note = {The version in the "Large Scale Kernel Machines" book is more up to date.},
  month_numeric = {4}
}