| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 536675 | Pattern Recognition Letters | 2008 | 6 Pages |
Abstract
We introduce a semi-supervised learning estimator which tends to the first kernel principal component as the number of labeled points vanishes. We show application of the proposed method for dimensionality reduction and develop a semi-supervised regression and classification algorithm for transductive inference.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Leonardo Angelini, Daniele Marinazzo, Mario Pellicoro, Sebastiano Stramaglia,