On the Jensen-Shannon divergence and variational distance

We study the distance measures between two probability distributions via two different distance metrics, a new metric induced from Jensen-Shannon divergence, and the well known L/sub 1/ metric. We show that several important results and constructions in computational complexity under the L/sub 1/ me...

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Veröffentlicht in:IEEE transactions on information theory 2005-09, Vol.51 (9), p.3333-3336
Hauptverfasser: TSAI, Shi-Chun, TZENG, Wen-Guey, WU, Hsin-Lung
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TZENG, Wen-Guey
WU, Hsin-Lung
description We study the distance measures between two probability distributions via two different distance metrics, a new metric induced from Jensen-Shannon divergence, and the well known L/sub 1/ metric. We show that several important results and constructions in computational complexity under the L/sub 1/ metric carry over to the new metric, such as Yao's next-bit predictor, the existence of extractors, the leftover hash lemma, and the construction of expander graph based extractor. Finally, we show that the useful parity lemma in studying pseudorandomness does not hold in the new metric.
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subjects Applied sciences
Complexity theory
Computation
Computational complexity
Computer science
Construction
Divergence
Exact sciences and technology
expander
Extractors
Extraterrestrial measurements
Graph theory
Graphs
Hash based algorithms
Information systems
Information theory
Information, signal and communications theory
Jensen-Shannon divergence
leftover hash lemma
Mutual information
Parity
parity lemma
Probability
Probability distribution
Sampling methods
Telecommunications and information theory
title On the Jensen-Shannon divergence and variational distance
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