@article{81449f07dd424549aedadde6aa92d7bd,
title = "Guessing with a bit of help",
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.",
keywords = "Boolean functions, Fourier analysis, Guessing moments, Guessing with a helper, Hypercontractivity, Maximum entropy, Strong data-processing inequalities",
author = "Nir Weinberger and Ofer Shayevitz",
note = "Publisher Copyright: {\textcopyright} 2019 by the authors.",
year = "2020",
month = jan,
day = "1",
doi = "10.3390/e22010039",
language = "אנגלית",
volume = "22",
pages = "39",
journal = "Entropy",
issn = "1099-4300",
publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",
number = "1",
}