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Kernel Methods for Implicit Surface Modeling

2005

Conference Paper

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We describe methods for computing an implicit model of a hypersurface that is given only by a finite sampling. The methods work by mapping the sample points into a reproducing kernel Hilbert space and then determining regions in terms of hyperplanes.

Author(s): Schölkopf, B. and Giesen, J. and Spalinger, S.
Book Title: Advances in Neural Information Processing Systems 17
Journal: Advances in Neural Information Processing Systems
Pages: 1193-1200
Year: 2005
Month: July
Day: 0
Editors: LK Saul and Y Weiss and L Bottou
Publisher: MIT Press

Department(s): Empirical Inference
Bibtex Type: Conference Paper (inproceedings)

Event Name: 18th Annual Conference on Neural Information Processing Systems (NIPS 2004)
Event Place: Vancouver, BC, Canada

Address: Cambridge, MA, USA
Digital: 0
ISBN: 0-262-19534-8
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

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BibTex

@inproceedings{2814,
  title = {Kernel Methods for Implicit Surface Modeling},
  author = {Sch{\"o}lkopf, B. and Giesen, J. and Spalinger, S.},
  journal = {Advances in Neural Information Processing Systems},
  booktitle = {Advances in Neural Information Processing Systems 17},
  pages = {1193-1200},
  editors = {LK Saul and  Y Weiss and  L Bottou},
  publisher = {MIT Press},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  address = {Cambridge, MA, USA},
  month = jul,
  year = {2005},
  month_numeric = {7}
}