Forward and Reverse Entropy Power Inequalities in Convex Geometry
arXiv:1604.04225 · doi:10.1007/978-1-4939-7005-6_14
Abstract
The entropy power inequality, which plays a fundamental role in information theory and probability, may be seen as an analogue of the Brunn-Minkowski inequality. Motivated by this connection to Convex Geometry, we survey various recent developments on forward and reverse entropy power inequalities not just for the Shannon-Boltzmann entropy but also more generally for Rényi entropy. In the process, we discuss connections between the so-called functional (or integral) and probabilistic (or entropic) analogues of some classical inequalities in geometric functional analysis
arXiv comment54 pages. Changes in v2: improved organization, cleaned up exposition, and numerous references added
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Cited by in corpus (27)
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- A lower bound on the differential entropy of log-concave random vectors with applications
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