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An Analysis of Inference with the Universum

2008

Conference Paper

ei


We study a pattern classification algorithm which has recently been proposed by Vapnik and coworkers. It builds on a new inductive principle which assumes that in addition to positive and negative data, a third class of data is available, termed the Universum. We assay the behavior of the algorithm by establishing links with Fisher discriminant analysis and oriented PCA, as well as with an SVM in a projected subspace (or, equivalently, with a data-dependent reduced kernel). We also provide experimental results.

Author(s): Sinz, FH. and Chapelle, O. and Agarwal, A. and Schölkopf, B.
Book Title: Advances in neural information processing systems 20
Journal: Advances in Neural Information Processing Systems 20: 21st Annual Conference on Neural Information Processing Systems 2007
Pages: 1369-1376
Year: 2008
Month: September
Day: 0
Editors: JC Platt and D Koller and Y Singer and S Roweis
Publisher: Curran

Department(s): Empirical Inference
Bibtex Type: Conference Paper (inproceedings)

Event Name: 21st Annual Conference on Neural Information Processing Systems (NIPS 2007)
Event Place: Vancouver, BC, Canada

Address: Red Hook, NY, USA
Digital: 0
ISBN: 978-1-605-60352-0
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

Links: PDF
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BibTex

@inproceedings{4709,
  title = {An Analysis of Inference with the Universum},
  author = {Sinz, FH. and Chapelle, O. and Agarwal, A. and Sch{\"o}lkopf, B.},
  journal = {Advances in Neural Information Processing Systems 20: 21st Annual Conference on Neural Information Processing Systems 2007},
  booktitle = {Advances in neural information processing systems 20},
  pages = {1369-1376},
  editors = {JC Platt and D Koller and Y Singer and S Roweis},
  publisher = {Curran},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  address = {Red Hook, NY, USA},
  month = sep,
  year = {2008},
  month_numeric = {9}
}