arXiv · 1912.07083
On Wyner's Common Information in the Gaussian Case
Abstract
Wyner's Common Information and a natural relaxation are studied in the special case of Gaussian random variables. The relaxation replaces conditional independence by a bound on the conditional mutual information. The main contribution is the proof that Gaussian auxiliaries are optimal, leading to a closed-form formula. As a corollary, the proof technique also establishes the optimality of Gaussian auxiliaries for the Gaussian Gray-Wyner network, a long-standing open problem.
Explore related subjects
Keep this discovery
Erixhen Sula, Michael Gastpar. 2019-12-15. On Wyner's Common Information in the Gaussian Case. https://arxiv.org/abs/1912.07083
Cite the original work for its findings. Save a collection to share your selection of sources.