Empirical Inference

Sampling Techniques for Kernel Methods

2002

Conference Paper

ei


We propose randomized techniques for speeding up Kernel Principal Component Analysis on three levels: sampling and quantization of the Gram matrix in training, randomized rounding in evaluating the kernel expansions, and random projections in evaluating the kernel itself. In all three cases, we give sharp bounds on the accuracy of the obtained approximations.

Author(s): Achlioptas, D. and McSherry, F. and Schölkopf, B.
Book Title: Advances in neural information processing systems 14
Journal: Advances in Neural Information Processing Systems
Pages: 335-342
Year: 2002
Month: September
Day: 0
Editors: TG Dietterich and S Becker and Z Ghahramani
Publisher: MIT Press

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

Event Name: 15th Annual Neural Information Processing Systems Conference (NIPS 2001)
Event Place: Vancouver, BC, Canada

Address: Cambridge, MA, USA
Digital: 0
ISBN: 0-262-04208-8
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

Links: PDF
Web

BibTex

@inproceedings{1856,
  title = {Sampling Techniques for Kernel Methods },
  author = {Achlioptas, D. and McSherry, F. and Sch{\"o}lkopf, B.},
  journal = {Advances in Neural Information Processing Systems},
  booktitle = {Advances in neural information processing systems 14 },
  pages = {335-342},
  editors = {TG Dietterich and S Becker and Z Ghahramani},
  publisher = {MIT Press},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  address = {Cambridge, MA, USA},
  month = sep,
  year = {2002},
  doi = {},
  month_numeric = {9}
}