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Guessing with a Bit of Help †

What is the value of just a few bits to a guesser? We study this problem in a setup where Alice wishes to guess an independent and identically distributed (i.i.d.) random vector and can procure a fixed number of k information bits from Bob, who has observed this vector through a memoryless channel....

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Detalles Bibliográficos
Autores principales: Weinberger, Nir, Shayevitz, Ofer
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516461/
https://www.ncbi.nlm.nih.gov/pubmed/33285814
http://dx.doi.org/10.3390/e22010039
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author Weinberger, Nir
Shayevitz, Ofer
author_facet Weinberger, Nir
Shayevitz, Ofer
author_sort Weinberger, Nir
collection PubMed
description What is the value of just a few bits to a guesser? We study this problem in a setup where Alice wishes to guess an independent and identically distributed (i.i.d.) random vector and can procure a fixed number of k information bits from Bob, who has observed this vector through a memoryless channel. We are interested in the guessing ratio, which we define as the ratio of Alice’s guessing-moments with and without observing Bob’s bits. For the case of a uniform binary vector observed through a binary symmetric channel, we provide two upper bounds on the guessing ratio by analyzing the performance of the dictator (for general [Formula: see text]) and majority functions (for [Formula: see text]). We further provide a lower bound via maximum entropy (for general [Formula: see text]) and a lower bound based on Fourier-analytic/hypercontractivity arguments (for [Formula: see text]). We then extend our maximum entropy argument to give a lower bound on the guessing ratio for a general channel with a binary uniform input that is expressed using the strong data-processing inequality constant of the reverse channel. We compute this bound for the binary erasure channel and conjecture that greedy dictator functions achieve the optimal guessing ratio.
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spelling pubmed-75164612020-11-09 Guessing with a Bit of Help † Weinberger, Nir Shayevitz, Ofer Entropy (Basel) Article What is the value of just a few bits to a guesser? We study this problem in a setup where Alice wishes to guess an independent and identically distributed (i.i.d.) random vector and can procure a fixed number of k information bits from Bob, who has observed this vector through a memoryless channel. We are interested in the guessing ratio, which we define as the ratio of Alice’s guessing-moments with and without observing Bob’s bits. For the case of a uniform binary vector observed through a binary symmetric channel, we provide two upper bounds on the guessing ratio by analyzing the performance of the dictator (for general [Formula: see text]) and majority functions (for [Formula: see text]). We further provide a lower bound via maximum entropy (for general [Formula: see text]) and a lower bound based on Fourier-analytic/hypercontractivity arguments (for [Formula: see text]). We then extend our maximum entropy argument to give a lower bound on the guessing ratio for a general channel with a binary uniform input that is expressed using the strong data-processing inequality constant of the reverse channel. We compute this bound for the binary erasure channel and conjecture that greedy dictator functions achieve the optimal guessing ratio. MDPI 2019-12-26 /pmc/articles/PMC7516461/ /pubmed/33285814 http://dx.doi.org/10.3390/e22010039 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Weinberger, Nir
Shayevitz, Ofer
Guessing with a Bit of Help †
title Guessing with a Bit of Help †
title_full Guessing with a Bit of Help †
title_fullStr Guessing with a Bit of Help †
title_full_unstemmed Guessing with a Bit of Help †
title_short Guessing with a Bit of Help †
title_sort guessing with a bit of help †
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516461/
https://www.ncbi.nlm.nih.gov/pubmed/33285814
http://dx.doi.org/10.3390/e22010039
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