Learning to Find Pre-Images
2004
Conference Paper
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We consider the problem of reconstructing patterns from a feature map. Learning algorithms using kernels to operate in a reproducing kernel Hilbert space (RKHS) express their solutions in terms of input points mapped into the RKHS. We introduce a technique based on kernel principal component analysis and regression to reconstruct corresponding patterns in the input space (aka pre-images) and review its performance in several applications requiring the construction of pre-images. The introduced technique avoids difficult and/or unstable numerical optimization, is easy to implement and, unlike previous methods, permits the computation of pre-images in discrete input spaces.
Author(s): | Bakir, GH. and Weston, J. and Schölkopf, B. |
Book Title: | Advances in Neural Information Processing Systems 16 |
Journal: | Advances in Neural Information Processing Systems |
Pages: | 449-456 |
Year: | 2004 |
Month: | June |
Day: | 0 |
Editors: | S Thrun and LK Saul and B Sch{\"o}lkopf |
Publisher: | MIT Press |
Department(s): | Empirische Inferenz |
Bibtex Type: | Conference Paper (inproceedings) |
Event Name: | 17th Annual Conference on Neural Information Processing Systems (NIPS 2003) |
Event Place: | Vancouver, BC, Canada |
Address: | Cambridge, MA, USA |
Digital: | 0 |
ISBN: | 0-262-20152-6 |
Organization: | Max-Planck-Gesellschaft |
School: | Biologische Kybernetik |
Links: |
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BibTex @inproceedings{2281, title = {Learning to Find Pre-Images}, author = {Bakir, GH. and Weston, J. and Sch{\"o}lkopf, B.}, journal = {Advances in Neural Information Processing Systems}, booktitle = {Advances in Neural Information Processing Systems 16}, pages = {449-456}, editors = {S Thrun and LK Saul and B Sch{\"o}lkopf}, publisher = {MIT Press}, organization = {Max-Planck-Gesellschaft}, school = {Biologische Kybernetik}, address = {Cambridge, MA, USA}, month = jun, year = {2004}, doi = {}, month_numeric = {6} } |