Collection Quantum Information Theory
Organizer(s)
Date(s)
11/12/2017
- 15/12/2017
Generalized maximum entropy estimation
We consider the problem of estimating a probability distribution that maximizes the entropy while satisfying a finite number of moment constraints, possibly corrupted by noise. Based on duality of convex programming, we present a novel approximation scheme using a smoothed fast gradient method that is equipped with explicit bounds on the approximation error. This is joint work with T. Sutter, P. Esfahani, and J. Lygeros (arXiv:1708. 07311).
