In this talk, I will present a generalization of Gurvits' capacity. This generalization is arrived at by viewing Gurvits' capacity through the lens of entropy. Subsequently, results from the geometry of polynomials and convex optimization are combined to show that this generalized capacity function can provide a deterministic approximate counting algorithm for a large class of discrete counting problems. Based on joint works with Damian Straszak.

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