PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

An Analysis of Inference with the Universum
F.H. Sinz, O. Chapelle, A. Agarwal and B. Schölkopf
In: Proceedings of the 20th Annual Conference on Neural Information Processing Systems (NIPS)(2007).


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.

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EPrint Type:Conference or Workshop Item (Spotlight)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:4033
Deposited By:Bernhard Schölkopf
Deposited On:25 February 2008