We derive in this paper a new Local Rademacher Complexity risk bound on the generalization ability of a model, which is able to take advantage of the availability of unlabeled samples. Moreover, this new bound improves state-of-the-art results even when no unlabeled samples are available.
Local Rademacher Complexity: Sharper risk bounds with and without unlabeled samples
ONETO, LUCA;GHIO, ALESSANDRO;RIDELLA, SANDRO;ANGUITA, DAVIDE
2015-01-01
Abstract
We derive in this paper a new Local Rademacher Complexity risk bound on the generalization ability of a model, which is able to take advantage of the availability of unlabeled samples. Moreover, this new bound improves state-of-the-art results even when no unlabeled samples are available.
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