Relative deviation learning bounds and generalization with unbounded loss functions View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-01

AUTHORS

Corinna Cortes, Spencer Greenberg, Mehryar Mohri

ABSTRACT

We present an extensive analysis of relative deviation bounds, including detailed proofs of two-sided inequalities and their implications. We also give detailed proofs of two-sided generalization bounds that hold in the general case of unbounded loss functions, under the assumption that a moment of the loss is bounded. We then illustrate how to apply these results in a sample application: the analysis of importance weighting. More... »

PAGES

1-26

References to SciGraph publications

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s10472-018-9613-y

    DOI

    http://dx.doi.org/10.1007/s10472-018-9613-y

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1111269990


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