English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Semi-Supervised Learning through Principal Directions Estimation

Chapelle, O., Schölkopf, B., & Weston, J. (2003). Semi-Supervised Learning through Principal Directions Estimation. In ICML 2003 Workshop on the Continuum from Labeled to Unlabeled Data in Machine Learning & Data Mining (pp. 1-7).

Item is

Files

show Files
hide Files
:
ICML-2003-Chapelle_.pdf (Any fulltext), 125KB
Name:
ICML-2003-Chapelle_.pdf
Description:
-
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show

Creators

show
hide
 Creators:
Chapelle, O1, 2, Author              
Schölkopf, B1, 2, Author              
Weston, J1, 2, Author              
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

Content

show
hide
Free keywords: -
 Abstract: We describe methods for taking into account unlabeled data in the training of a kernel-based classifier, such as a Support Vector Machines (SVM). We propose two approaches utilizing unlabeled points in the vicinity of labeled ones. Both of the approaches effectively modify the metric of the pattern space, either by using non-spherical Gaussian density estimates which are determined using EM, or by modifying the kernel function using displacement vectors computed from pairs of unlabeled and labeled points. The latter is linked to techniques for training invariant SVMs. We present experimental results indicating that the proposed technique can lead to substantial improvements of classification accuracy.

Details

show
hide
Language(s):
 Dates: 2003-08
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 2168
 Degree: -

Event

show
hide
Title: ICML 2003 Workshop on the Continuum from Labeled to Unlabeled Data in Machine Learning & Data Mining
Place of Event: Washington, DC, USA
Start-/End Date: 2003-08-21

Legal Case

show

Project information

show

Source 1

show
hide
Title: ICML 2003 Workshop on the Continuum from Labeled to Unlabeled Data in Machine Learning & Data Mining
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 1 - 7 Identifier: -