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 ρ (Hamming distance <i>d</i>ċ 1−ρ&frac;2), how quickly can one find the two correlated vectors? We present an algorithm which, forâ€¦Â (More)

@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}
}