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On the Pre-Image Problem in Kernel Methods
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.
@inbook{3608, title = {On the Pre-Image Problem in Kernel Methods}, booktitle = {Kernel Methods in Bioengineering, Signal and Image Processing}, abstract = {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.}, pages = {284-302}, editors = {G Camps-Valls and JL Rojo-\'{A}lvarez and M Mart\'{i}nez-Ram\'{o}n}, publisher = {Idea Group Publishing}, organization = {Max-Planck-Gesellschaft}, school = {Biologische Kybernetik}, address = {Hershey, PA, USA}, month = jan, year = {2007}, slug = {3608}, author = {BakIr, G. and Sch{\"o}lkopf, B. and Weston, J.}, month_numeric = {1} }
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