Learning relatively small classes

Shahar Mendelson*

*Corresponding author for this work

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

    6 Citations (Scopus)

    Abstract

    We study the sample complexity of proper and improper learning problems with respect to different Lq loss functions. We improve the known estimates for classes which have relatively small covering numbers (log-covering numbers which are polynomial with exponent p < 2) with respect to the Lq norm for q ≥ 2.

    Original languageEnglish
    Title of host publicationComputational Learning Theory - 14th Annual Conference on Computational Learning Theory, COLT 2001 and 5th European Conference on Computational Learning Theory, EuroCOLT 2001, Proceedings
    EditorsDavid Helmbold, Bob Williamson
    PublisherSpringer Verlag
    Pages273-288
    Number of pages16
    ISBN (Print)9783540423430
    DOIs
    Publication statusPublished - 2001
    Event14th Annual Conference on Computational Learning Theory, COLT 2001 and 5th European Conference on Computational Learning Theory, EuroCOLT 2001 - Amsterdam, Netherlands
    Duration: 16 Jul 200119 Jul 2001

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume2111
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference14th Annual Conference on Computational Learning Theory, COLT 2001 and 5th European Conference on Computational Learning Theory, EuroCOLT 2001
    Country/TerritoryNetherlands
    CityAmsterdam
    Period16/07/0119/07/01

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