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An Augmented PAC Model for Semi-Supervised Learningedited by: Olivier Chapelle, Bernhard Schölkopf, Alexander Zien |
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Notes for this articleExtends usual PAC analysis to an new framework involving a "compatibility function" that measures how well adapted a function is to the distribution generating the unlabelled data.
Intuitively, the smaller the compatible part of a function class is w.r.t. the unlabelled distribution the easier it is to identify a good generalisation of the labelled data.
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