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Bibliographic Details
Main Authors: Bhattacharya, Sagnik, Narayan, Prakash
Format: Preprint
Published: 2023
Subjects:
Online Access:https://arxiv.org/abs/2307.15844
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author Bhattacharya, Sagnik
Narayan, Prakash
author_facet Bhattacharya, Sagnik
Narayan, Prakash
contents Shared information is a measure of mutual dependence among multiple jointly distributed random variables with finite alphabets. For a Markov chain on a tree with a given joint distribution, we give a new proof of an explicit characterization of shared information. The Markov chain on a tree is shown to possess a global Markov property based on graph separation; this property plays a key role in our proofs. When the underlying joint distribution is not known, we exploit the special form of this characterization to provide a multiarmed bandit algorithm for estimating shared information, and analyze its error performance.
format Preprint
id arxiv_https___arxiv_org_abs_2307_15844
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Shared Information for a Markov Chain on a Tree
Bhattacharya, Sagnik
Narayan, Prakash
Information Theory
Shared information is a measure of mutual dependence among multiple jointly distributed random variables with finite alphabets. For a Markov chain on a tree with a given joint distribution, we give a new proof of an explicit characterization of shared information. The Markov chain on a tree is shown to possess a global Markov property based on graph separation; this property plays a key role in our proofs. When the underlying joint distribution is not known, we exploit the special form of this characterization to provide a multiarmed bandit algorithm for estimating shared information, and analyze its error performance.
title Shared Information for a Markov Chain on a Tree
topic Information Theory
url https://arxiv.org/abs/2307.15844