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Information Geometric Approach on Most Informative Boolean Function Conjecture
Let [Formula: see text] be a memoryless uniform Bernoulli source and [Formula: see text] be the output of it through a binary symmetric channel. Courtade and Kumar conjectured that the Boolean function [Formula: see text] that maximizes the mutual information [Formula: see text] is a dictator functi...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7513214/ https://www.ncbi.nlm.nih.gov/pubmed/33265777 http://dx.doi.org/10.3390/e20090688 |
Sumario: | Let [Formula: see text] be a memoryless uniform Bernoulli source and [Formula: see text] be the output of it through a binary symmetric channel. Courtade and Kumar conjectured that the Boolean function [Formula: see text] that maximizes the mutual information [Formula: see text] is a dictator function, i.e., [Formula: see text] for some i. We propose a clustering problem, which is equivalent to the above problem where we emphasize an information geometry aspect of the equivalent problem. Moreover, we define a normalized geometric mean of measures and interesting properties of it. We also show that the conjecture is true when the arithmetic and geometric mean coincide in a specific set of measures. |
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