Learning Semi-Riemannian Metrics for Semisupervised Feature Extraction

Abstract

Discriminant feature extraction plays a central role in pattern recognition and classification. Linear Discriminant Analysis (LDA) is a traditional algorithm for supervised feature extraction. Recently, unlabeled data have been utilized to improve LDA. However, the intrinsic problems of LDA still exist and only the similarity among the unlabeled data is… (More)
DOI: 10.1109/TKDE.2010.143

10 Figures and Tables

Topics

  • Presentations referencing similar topics