• DocumentCode
    787372
  • Title

    A distribution dependent refinement of Pinsker´s inequality

  • Author

    Ordentlich, Erik ; Weinberger, Marcelo J.

  • Author_Institution
    Hewlett-Packard Labs., Palo Alto, CA, USA
  • Volume
    51
  • Issue
    5
  • fYear
    2005
  • fDate
    5/1/2005 12:00:00 AM
  • Firstpage
    1836
  • Lastpage
    1840
  • Abstract
    Given two probability distributions Q and P, let ||Q-P||1 and D(Q||P), respectively, denote the L1 distance and divergence between Q and P. We derive a refinement of Pinsker´s inequality of the form D(Q||P)≥c(P)||Q-P||12 and characterize the best P-dependent factor c(P). We apply the refined inequality to large deviations and measure concentration.
  • Keywords
    information theory; probability; Hoeffding inequality; P-dependent factor; Pinsker inequality; Sanov theorem; distribution dependent refinement; measure concentration; probability distribution; Pattern recognition; Probability distribution; Statistical learning; Divergence; Hoeffding´s inequality; Pinsker´s inequality; Sanov´s theorem; measure concentration;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/TIT.2005.846407
  • Filename
    1424321
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=787372