TY - UNPB
T1 - An optimal approximation of discrete random variables with respect to the Kolmogorov distance.
AU - Cohen, Liat
AU - Fried, Dror
AU - Weiss, Gera
N1 - DBLP's bibliographic metadata records provided through http://dblp.org/search/publ/api are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.
PY - 2018
Y1 - 2018
N2 - We present an algorithm that takes a discrete random variable X and a number m and computes a random variable whose support (set of possible outcomes) is of size at most m and whose Kolmogorov distance from X is minimal. In addition to a formal theoretical analysis of the correctness and of the computational complexity of the algorithm, we present a detailed empirical evaluation that shows how the proposed approach performs in practice in different applications and domains.
AB - We present an algorithm that takes a discrete random variable X and a number m and computes a random variable whose support (set of possible outcomes) is of size at most m and whose Kolmogorov distance from X is minimal. In addition to a formal theoretical analysis of the correctness and of the computational complexity of the algorithm, we present a detailed empirical evaluation that shows how the proposed approach performs in practice in different applications and domains.
U2 - 10.48550/arXiv.1805.07535
DO - 10.48550/arXiv.1805.07535
M3 - Preprint
BT - An optimal approximation of discrete random variables with respect to the Kolmogorov distance.
ER -