• DocumentCode
    1780667
  • Title

    Sublinear algorithms for outlier detection and generalized closeness testing

  • Author

    Acharya, Jayadev ; Jafarpour, Ashkan ; Orlitsky, Alon ; Suresh, A.T.

  • Author_Institution
    ECE Dept., Univ. of California, San Diego, La Jolla, CA, USA
  • fYear
    2014
  • fDate
    June 29 2014-July 4 2014
  • Firstpage
    3200
  • Lastpage
    3204
  • Abstract
    Outlier detection is the problem of finding a few different distributions in a set of mostly identical ones. Closeness testing is the problem of deciding whether two distributions are identical or different. We relate the two problems, construct a sub-linear generalized closeness test for unequal sample lengths, and use this result to derive a sub-linear universal outlier detector. We also lower bound the sample complexity of both problems.
  • Keywords
    statistical distributions; statistical testing; generalized closeness testing; outlier detection; sample complexity; sub-linear universal outlier detector; sublinear algorithm; unequal sample length; Algorithm design and analysis; Complexity theory; Detectors; Error probability; Information theory; Random variables; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory (ISIT), 2014 IEEE International Symposium on
  • Conference_Location
    Honolulu, HI
  • Type

    conf

  • DOI
    10.1109/ISIT.2014.6875425
  • Filename
    6875425