nips nips2003 nips2003-113 nips2003-113-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Dengyong Zhou, Olivier Bousquet, Thomas N. Lal, Jason Weston, Bernhard Schölkopf
Abstract: We consider the general problem of learning from labeled and unlabeled data, which is often called semi-supervised learning or transductive inference. A principled approach to semi-supervised learning is to design a classifying function which is sufficiently smooth with respect to the intrinsic structure collectively revealed by known labeled and unlabeled points. We present a simple algorithm to obtain such a smooth solution. Our method yields encouraging experimental results on a number of classification problems and demonstrates effective use of unlabeled data. 1
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