On the Pre-Image Problem in Kernel Methods

BakIr, G; Schölkopf, B; Weston, J; Camps-Valls,; G.,; Rojo-Álvarez, J. L.; Martínez-Ramón, M.

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On the Pre-Image Problem in Kernel Methods

BakIr, G., Schölkopf, B., & Weston, J. (2007). On the Pre-Image Problem in Kernel Methods. In Kernel Methods in Bioengineering, Signal and Image Processing (pp. 284-302). Hershey, PA, USA: Idea Group Publishing.

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Datensatz-Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-CEFB-1 Versions-Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-CEFC-0

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BakIr, G¹, Autor
Schölkopf, B¹, Autor
Weston, J¹, Autor
Camps-Valls, Herausgeber
G., Herausgeber
Rojo-Álvarez, J. L., Herausgeber
Martínez-Ramón, M., Herausgeber

Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795

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Zusammenfassung: In this chapter we are concerned with the problem of reconstructing patterns from their representation in feature space, known as the pre-image problem. We review existing algorithms and propose a learning based approach. All algorithms are discussed regarding their usability and complexity and evaluated on an image denoising application.