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
Link To Document :
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