Surrogate regret bounds for proper losses

Mark D. Reid, Robert C. Williamson

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    34 Citations (Scopus)

    Abstract

    We present tight surrogate regret bounds for the class of proper (i.e., Fisher consistent) losses. The bounds generalise the margin-based bounds due to Bartlett et al. (2006). The proof uses Taylor's theorem and leads to new representations for loss and regret and a simple proof of the integral representation of proper losses. We also present a different formulation of a duality result of Bregman divergences which leads to a simple demonstration of the convexity of composite losses using canonical link functions.

    Original languageEnglish
    Title of host publicationProceedings of the 26th International Conference On Machine Learning, ICML 2009
    Pages897-904
    Number of pages8
    Publication statusPublished - 2009
    Event26th International Conference On Machine Learning, ICML 2009 - Montreal, QC, Canada
    Duration: 14 Jun 200918 Jun 2009

    Publication series

    NameProceedings of the 26th International Conference On Machine Learning, ICML 2009

    Conference

    Conference26th International Conference On Machine Learning, ICML 2009
    Country/TerritoryCanada
    CityMontreal, QC
    Period14/06/0918/06/09

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