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Combining labeled and unlabeled data with co-training

We consider the problem of using a large unlabeled sample to boost performance of a learning algorit,hrn when only a small set of labeled examples is available.

Avrim Blum, Tom M. Mitchell

https://resea.org/10.1145/279943.279962

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Abstract

We consider the problem of using a large unlabeled sample to boost performance of a learning algorit,hrn when only a small set of labeled examples is available.