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9

NIPS
2004

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Semi-supervised Learning via Gaussian Processes

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Semi-supervised Learning via Gaussian Processes

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We present a probabilistic approach to learning a Gaussian Process classifier in the presence of unlabeled data. Our approach involves a "null category noise model" (NCNM) inspired by ordered categorical noise models. The noise model reflects an assumption that the data density is lower between the class-conditional densities. We illustrate our approach on a toy problem and present comparative results for the semi-supervised classification of handwritten digits.

Neil D. Lawrence, Michael I. Jordan

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Added	31 Oct 2010
Updated	31 Oct 2010
Type	Conference
Year	2004
Where	NIPS
Authors	Neil D. Lawrence, Michael I. Jordan

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