An optimal approximation of discrete random variables with respect to the Kolmogorov distance
May 19, 2018 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Liat Cohen, Dror Fried, Gera Weiss
arXiv ID
1805.07535
Category
cs.DS: Data Structures & Algorithms
Cross-listed
cs.AI
Citations
1
Venue
arXiv.org
Last Checked
4 months ago
Abstract
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.
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