Learning classifiers on a partially labeled data manifold

Liu Qiuhua, Liao Xuejun, Lawrence Carin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present an algorithm for learning parametric classifiers on a partially labeled data manifold, based on a graph representation of the manifold. The unlabeled data are utilized by basing classifier learning on neighborhoods, formed via Markov random, walks. The proposed algorithm, yields superior performance on three benchmark data sets and the margin of improvements over existing semi-supervised algorithms is significant. © 2007 IEEE.
Original languageEnglish (US)
Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
DOIs
StatePublished - Aug 6 2007
Externally publishedYes

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