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Testing random variables for independence and identity
 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
, 2000
"... Given access to independent samples of a distribution �over�℄�℄, we show how to test whether the distributions formed by projecting�to each coordinate are independent, i.e., whether�isclose in the norm to the product distribution��for some distributions�over �℄and�over�℄. The sample complexity of o ..."
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Cited by 78 (20 self)
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Given access to independent samples of a distribution �over�℄�℄, we show how to test whether the distributions formed by projecting�to each coordinate are independent, i.e., whether�isclose in the norm to the product distribution��for some distributions�over �℄and�over�℄. The sample complexity
Testing Random Variables for Independence and Identity
, 2001
"... Given access to independent samples of a distribution A over [n] [m], we show how to test whether the distributions formed by projecting A to each coordinate are independent, i.e., whether A is close in the L 1 norm to the product distribution A 1 A 2 for some distributions A 1 over [n] and A 2 ov ..."
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Given access to independent samples of a distribution A over [n] [m], we show how to test whether the distributions formed by projecting A to each coordinate are independent, i.e., whether A is close in the L 1 norm to the product distribution A 1 A 2 for some distributions A 1 over [n] and A 2
Testing random variables for independence and identity
, 2003
"... Given access to independent samples of a distributionA over [n] [m], we show how to test whether the distributions formed by projecting A to each coordinate are independent, i.e., whether A is close in the L1 norm to the product distribution A1 A2 for some distributions A1 over [n] and A2 over [m] ..."
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Given access to independent samples of a distributionA over [n] [m], we show how to test whether the distributions formed by projecting A to each coordinate are independent, i.e., whether A is close in the L1 norm to the product distribution A1 A2 for some distributions A1 over [n] and A2 over [m
Testing random variables for independence and identity Tu*gkan Batu
"... Abstract Given access to independent samples of a distribution A over [n] \Theta [m], we show how to test whether the distributions formed by projecting A to each coordinate are independent, i.e., whether A is fflclose in the L1 norm to theproduct distribution A1 \Theta A2 for some distributions ..."
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Abstract Given access to independent samples of a distribution A over [n] \Theta [m], we show how to test whether the distributions formed by projecting A to each coordinate are independent, i.e., whether A is fflclose in the L1 norm to theproduct distribution A1 \Theta A2 for some distributions
Testing random variables for independence and identity Tu*gkan Batu
"... Abstract Given access to independent samples of a distribution A over [n] \Theta [m], we show how to test whether the distributions formed by projecting A to each coordinate are independent, i.e., whether A is fflclose in the L1 norm to theproduct distribution A1 \Theta A2 for some distributions ..."
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Abstract Given access to independent samples of a distribution A over [n] \Theta [m], we show how to test whether the distributions formed by projecting A to each coordinate are independent, i.e., whether A is fflclose in the L1 norm to theproduct distribution A1 \Theta A2 for some distributions
DART: Directed automated random testing
 In Programming Language Design and Implementation (PLDI
, 2005
"... We present a new tool, named DART, for automatically testing software that combines three main techniques: (1) automated extraction of the interface of a program with its external environment using static sourcecode parsing; (2) automatic generation of a test driver for this interface that performs ..."
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Cited by 823 (41 self)
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that performs random testing to simulate the most general environment the program can operate in; and (3) dynamic analysis of how the program behaves under random testing and automatic generation of new test inputs to direct systematically the execution along alternative program paths. Together, these three
High confidence visual recognition of persons by a test of statistical independence
 IEEE Trans. on Pattern Analysis and Machine Intelligence
, 1993
"... Abstruct A method for rapid visual recognition of personal identity is described, based on the failure of a statistical test of independence. The most unique phenotypic feature visible in a person’s face is the detailed texture of each eye’s iris: An estimate of its statistical complexity in a samp ..."
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Cited by 596 (8 self)
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Abstruct A method for rapid visual recognition of personal identity is described, based on the failure of a statistical test of independence. The most unique phenotypic feature visible in a person’s face is the detailed texture of each eye’s iris: An estimate of its statistical complexity in a
An introduction to variable and feature selection
 Journal of Machine Learning Research
, 2003
"... Variable and feature selection have become the focus of much research in areas of application for which datasets with tens or hundreds of thousands of variables are available. ..."
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Cited by 1283 (16 self)
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Variable and feature selection have become the focus of much research in areas of application for which datasets with tens or hundreds of thousands of variables are available.
Randomized Algorithms
, 1995
"... Randomized algorithms, once viewed as a tool in computational number theory, have by now found widespread application. Growth has been fueled by the two major benefits of randomization: simplicity and speed. For many applications a randomized algorithm is the fastest algorithm available, or the simp ..."
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Cited by 2210 (37 self)
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Randomized algorithms, once viewed as a tool in computational number theory, have by now found widespread application. Growth has been fueled by the two major benefits of randomization: simplicity and speed. For many applications a randomized algorithm is the fastest algorithm available
Fast probabilistic algorithms for verification of polynomial identities
 J. ACM
, 1980
"... ABSTRACT The starthng success of the RabmStrassenSolovay pnmahty algorithm, together with the intriguing foundattonal posstbthty that axtoms of randomness may constttute a useful fundamental source of mathemaucal truth independent of the standard axmmaUc structure of mathemaUcs, suggests a wgorous ..."
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Cited by 533 (1 self)
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ABSTRACT The starthng success of the RabmStrassenSolovay pnmahty algorithm, together with the intriguing foundattonal posstbthty that axtoms of randomness may constttute a useful fundamental source of mathemaucal truth independent of the standard axmmaUc structure of mathemaUcs, suggests a
Results 1  10
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