• DocumentCode
    1969255
  • Title

    Universal outlier detection

  • Author

    Yun Li ; Nitinawarat, S. ; Veeravalli, Venugopal V.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
  • fYear
    2013
  • fDate
    10-15 Feb. 2013
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    The following outlier detection problem is studied in a universal setting. Vector observations are collected each with M coordinates. When the i-th coordinate is the outlier, the observations in that coordinate are assumed to be distributed according to the “outlier” distribution, distinct from the common “typical” distribution governing the observations in all the other coordinates. Nothing is known about the outlier and the typical distributions except that they are distinct and have full supports. The goal is to design a universal detector to best discern the outlier coordinate. A universal detector is proposed and is shown to be universally exponentially consistent, and a single-letter characterization of the exponent for a symmetric error criterion achievable by this detector is derived. An upper bound for the error exponent that applies to any universal detector is also derived. For the special case of M = 3, a tighter upper bound is derived that quantifies the loss in the exponent when the knowledge of the outlier and typical distributions is absent, from when they are known.
  • Keywords
    inference mechanisms; vectors; outlier coordinate; universal outlier detection; vector observation; Detectors; Probabilistic logic; Random variables; Testing; Training data; Upper bound; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory and Applications Workshop (ITA), 2013
  • Conference_Location
    San Diego, CA
  • Print_ISBN
    978-1-4673-4648-1
  • Type

    conf

  • DOI
    10.1109/ITA.2013.6502997
  • Filename
    6502997