Finding Correlations in Subquadratic Time, with Applications to Learning Parities and the Closest Pair Problem

Abstract

Given a set of <i>n</i> <i>d</i>-dimensional Boolean vectors with the promise that the vectors are chosen uniformly at random with the exception of two vectors that have Pearson correlation coefficient &rho; (Hamming distance <i>d</i>&#267; 1&minus;&rho;&frac;2), how quickly can one find the two correlated vectors&quest; We present an algorithm which, for… (More)
DOI: 10.1145/2728167

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@article{Valiant2015FindingCI, title={Finding Correlations in Subquadratic Time, with Applications to Learning Parities and the Closest Pair Problem}, author={Gregory Valiant}, journal={J. ACM}, year={2015}, volume={62}, pages={13:1-13:45} }