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Entropy inequalities for sums and applications

Date: 
Monday 23rd June 2008 - 15:40 to 16:20
Abstract: 

A large class of entropy inequalities is developed for sums of random vectors, giving both lower and upper bounds for the entropy of a sum. These inequalities are combinatorial in nature, being indexed by hypergraphs, and have fruitful applications to probability and information theory. One consequence is monotonicity behaviors in limit theorems, including for the entropy in the classical central limit theorem, and for relevant functionals in laws of large numbers for certain random matrix models.

Related Links

University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons