Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Conferences, Workshops, Symposiums, and Seminars
  4. Bayesian Model Selection for Support Vector Machines, Gaussian Processes and Other Kernel Classifiers
 
conference paper

Bayesian Model Selection for Support Vector Machines, Gaussian Processes and Other Kernel Classifiers

Seeger, Matthias  
Solla, S.
•
Leen, T.
Show more
2000
Proceedings of the 13th Annual Conference on Neural Information Processing Systems
Neural Information Processing Systems 12

We present a variational Bayesian method for model selection over families of kernels classifiers like Support Vector machines or Gaussian processes. The algorithm needs no user interaction and is able to adapt a large number of kernel parameters to given data without having to sacrifice training cases for validation. This opens the possibility to use sophisticated families of kernels in situations where the small ``standard kernel'' classes are clearly inappropriate. We relate the method to other work done on Gaussian processes and clarify the relation between Support Vector machines and certain Gaussian process models.

  • Files
  • Details
  • Metrics
Loading...
Thumbnail Image
Name

nips-paper.pdf

Access type

openaccess

Size

806.83 KB

Format

Adobe PDF

Checksum (MD5)

ee04935b65046a318152c34f398b1808

Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés