Abstract
Using techniques from Statistical Physics, the annealed VC entropy for hyperplanes in high dimensional spaces is calculated as a function of the margin for a spherical Gaussian distribution of inputs.
| Original language | English |
|---|---|
| Title of host publication | Advances in Kernel Methods - Support vector learning |
| Editors | Bernhard Scholkopf, Christopher J. C. Burges, Alexander J. Smola |
| Place of Publication | Cambridge, MA |
| Publisher | MIT |
| Pages | 117-126 |
| Number of pages | 10 |
| ISBN (Print) | 0262194163 |
| Publication status | Published - 18 Dec 1998 |
Bibliographical note
Copyright of the Massachusetts Institute of Technology Press (MIT Press) Available in Google BooksKeywords
- annealed VC entropy
- hyperplanes
- high dimensional spaces
- spherical Gaussian distribution
Fingerprint
Dive into the research topics of 'On the annealed VC entropy for margin classifiers: A statistical mechanics study'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver