IST Lunch Bunch

Tuesday February 24, 2015 12:00 PM

Relative Entropy Optimization and Its Applications

Speaker: Venkat Chandrasekaran, Computing and Mathematical Sciences and Electrical Engineering, Caltech
Location: Annenberg 105

Relative entropy programs (REPs) are optimization problems specified via linear and relative entropy inequalities.  REPs are convex programs as the relative entropy function is jointly convex with respect to both its arguments.  Prominent families of convex programs such as geometric programs (GPs),  second-order cone programs (SOCPs), and entropy maximization problems are special cases of REPs, although REPs are more general than these classes of problems.  We describe solutions based on REPs to a range of problems such as permanent maximization, robust optimization formulations of GPs, and hitting-time estimation in dynamical systems.  We conclude with a discussion of quantum relative entropy optimization problems, including a review of the similarities and distinctions with respect to the classical case.

Series IST Lunch Bunch

Contact: Christine Ortega at 626.395.2076 cortega@caltech.edu