skip to main content

IST Lunch Bunch

Tuesday, February 24, 2015
12:00pm to 1:00pm
Add to Cal
Annenberg 105
Relative Entropy Optimization and Its Applications
Venkat Chandrasekaran, Assistant Professor, Computing and Mathematical Sciences and Electrical Engineering, Caltech,

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.

For more information, please contact Christine Ortega by phone at 626.395.2076 or by email at [email protected].