Discriminative Dimensionality Reduction Mappings
Gisbrecht A, Hofmann D, Hammer B (2012)
In: Advances in Intelligent Data Analysis XI. Hollmén J, Klawonn F, Tucker A (Eds); Lecture Notes in Computer Science. Berlin, Heidelberg: Springer Berlin Heidelberg: 126-138.
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Herausgeber*in
Hollmén, Jaakko;
Klawonn, Frank;
Tucker, Allan
Abstract / Bemerkung
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.
Erscheinungsjahr
2012
Buchtitel
Advances in Intelligent Data Analysis XI
Serientitel
Lecture Notes in Computer Science
Seite(n)
126-138
ISBN
978-3-642-34155-7
eISBN
978-3-642-34156-4
ISSN
0302-9743
eISSN
1611-3349
Page URI
https://pub.uni-bielefeld.de/record/2982106
Zitieren
Gisbrecht A, Hofmann D, Hammer B. Discriminative Dimensionality Reduction Mappings. In: Hollmén J, Klawonn F, Tucker A, eds. Advances in Intelligent Data Analysis XI. Lecture Notes in Computer Science. Berlin, Heidelberg: Springer Berlin Heidelberg; 2012: 126-138.
Gisbrecht, A., Hofmann, D., & Hammer, B. (2012). Discriminative Dimensionality Reduction Mappings. In J. Hollmén, F. Klawonn, & A. Tucker (Eds.), Lecture Notes in Computer Science. Advances in Intelligent Data Analysis XI (pp. 126-138). Berlin, Heidelberg: Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-34156-4_13
Gisbrecht, Andrej, Hofmann, Daniela, and Hammer, Barbara. 2012. “Discriminative Dimensionality Reduction Mappings”. In Advances in Intelligent Data Analysis XI, ed. Jaakko Hollmén, Frank Klawonn, and Allan Tucker, 126-138. Lecture Notes in Computer Science. Berlin, Heidelberg: Springer Berlin Heidelberg.
Gisbrecht, A., Hofmann, D., and Hammer, B. (2012). “Discriminative Dimensionality Reduction Mappings” in Advances in Intelligent Data Analysis XI, Hollmén, J., Klawonn, F., and Tucker, A. eds. Lecture Notes in Computer Science (Berlin, Heidelberg: Springer Berlin Heidelberg), 126-138.
Gisbrecht, A., Hofmann, D., & Hammer, B., 2012. Discriminative Dimensionality Reduction Mappings. In J. Hollmén, F. Klawonn, & A. Tucker, eds. Advances in Intelligent Data Analysis XI. Lecture Notes in Computer Science. Berlin, Heidelberg: Springer Berlin Heidelberg, pp. 126-138.
A. Gisbrecht, D. Hofmann, and B. Hammer, “Discriminative Dimensionality Reduction Mappings”, Advances in Intelligent Data Analysis XI, J. Hollmén, F. Klawonn, and A. Tucker, eds., Lecture Notes in Computer Science, Berlin, Heidelberg: Springer Berlin Heidelberg, 2012, pp.126-138.
Gisbrecht, A., Hofmann, D., Hammer, B.: Discriminative Dimensionality Reduction Mappings. In: Hollmén, J., Klawonn, F., and Tucker, A. (eds.) Advances in Intelligent Data Analysis XI. Lecture Notes in Computer Science. p. 126-138. Springer Berlin Heidelberg, Berlin, Heidelberg (2012).
Gisbrecht, Andrej, Hofmann, Daniela, and Hammer, Barbara. “Discriminative Dimensionality Reduction Mappings”. Advances in Intelligent Data Analysis XI. Ed. Jaakko Hollmén, Frank Klawonn, and Allan Tucker. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. Lecture Notes in Computer Science. 126-138.
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