Literature DB >> 33285814

Guessing with a Bit of Help.

Nir Weinberger1, Ofer Shayevitz2.   

Abstract

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 k ≥ 1 ) and majority functions (for k = 1 ). We further provide a lower bound via maximum entropy (for general k ≥ 1 ) and a lower bound based on Fourier-analytic/hypercontractivity arguments (for k = 1 ). 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.

Entities:  

Keywords:  boolean functions; fourier analysis; guessing moments; guessing with a helper; hypercontractivity; maximum entropy; strong data-processing inequalities

Year:  2019        PMID: 33285814      PMCID: PMC7516461          DOI: 10.3390/e22010039

Source DB:  PubMed          Journal:  Entropy (Basel)        ISSN: 1099-4300            Impact factor:   2.524


  1 in total

1.  Exploiting the Massey Gap.

Authors:  Andrei Tănăsescu; Pantelimon George Popescu
Journal:  Entropy (Basel)       Date:  2020-12-11       Impact factor: 2.524

  1 in total

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