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Semi-supervised learning using Gaussian fields and harmonic functions

by: X Zhu, Z Ghahramani, J Lafferty

(2003)

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fields, gaussian, learning, random, semi_supervised, semi-supervised

Abstract

An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, with edge weights encoding the similarity between instances.

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