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41st Annual Symposium on Foundations of Computer Science
Testing that distributions are close
Redondo Beach, California
November 12-November 14
ISBN: 0-7695-0850-2
| ASCII Text | x | ||
| T. Batu, L. Fortnow, R. Rubinfeld, W.D. Smith, P. White, "Testing that distributions are close," Foundations of Computer Science, IEEE Annual Symposium on, pp. 259, 41st Annual Symposium on Foundations of Computer Science, 2000. | |||
| BibTex | x | ||
| @article{ 10.1109/SFCS.2000.892113, author = {T. Batu and L. Fortnow and R. Rubinfeld and W.D. Smith and P. White}, title = {Testing that distributions are close}, journal ={Foundations of Computer Science, IEEE Annual Symposium on}, volume = {0}, year = {2000}, issn = {0272-5428}, pages = {259}, doi = {http://doi.ieeecomputersociety.org/10.1109/SFCS.2000.892113}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - Foundations of Computer Science, IEEE Annual Symposium on TI - Testing that distributions are close SN - 0272-5428 SP EP A1 - T. Batu, A1 - L. Fortnow, A1 - R. Rubinfeld, A1 - W.D. Smith, A1 - P. White, PY - 2000 KW - sampling methods; Markov processes; probability; computational complexity; distribution closeness testing; sampling; sublinear algorithm; lower bound; Markov process; rapidly mixing process; sublinear algorithms; probability VL - 0 JA - Foundations of Computer Science, IEEE Annual Symposium on ER - | |||
Given two distributions over an n element set, we wish to check whether these distributions are statistically close by only sampling. We give a sublinear algorithm which uses O(n/sup 2/3//spl epsiv//sup -4/ log n) independent samples from each distribution, runs in time linear in the sample size, makes no assumptions about the structure of the distributions, and distinguishes the cases when the distance between the distributions is small (less than max(/spl epsiv//sup 2//32/sup 3//spl radic/n,/spl epsiv//4/spl radic/n=)) or large (more than /spl epsiv/) in L/sub 1/-distance. We also give an /spl Omega/(n/sup 2/3//spl epsiv//sup -2/3/) lower bound. Our algorithm has applications to the problem of checking whether a given Markov process is rapidly mixing. We develop sublinear algorithms for this problem as well.
Index Terms:
sampling methods; Markov processes; probability; computational complexity; distribution closeness testing; sampling; sublinear algorithm; lower bound; Markov process; rapidly mixing process; sublinear algorithms; probability
Citation:
T. Batu, L. Fortnow, R. Rubinfeld, W.D. Smith, P. White, "Testing that distributions are close," focs, pp.259, 41st Annual Symposium on Foundations of Computer Science, 2000
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