Discriminative dimensionality reduction mappings

Authors:
Andrej Gisbrecht;Daniela Hofmann;Barbara Hammer
Affiliations:
CITEC Centre of Excellence, University of Bielefeld, Germany;CITEC Centre of Excellence, University of Bielefeld, Germany;CITEC Centre of Excellence, University of Bielefeld, Germany
Venue:
IDA'12 Proceedings of the 11th international conference on Advances in Intelligent Data Analysis
Year:
2012

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Abstract

Discriminative dimensionality reduction aims at a low dimensional, usually nonlinear representation of given data such that information as specified by auxiliary discriminative labeling is presented as accurately as possible. This paper centers around two open problems connected to this question: (i) how to evaluate discriminative dimensionality reduction quantitatively? (ii) how to arrive at explicit nonlinear discriminative dimensionality reduction mappings? Based on recent work for the unsupervised case, we propose an evaluation measure and an explicit discriminative dimensionality reduction mapping using the Fisher information.