Lecture: "OSQP: An operator splitting solver for quadratic programs"

Abstract:

Quadratic programs are a class of convex optimization problems which arise in numerous applications. Although interior-point methods can in principle solve these problems efficiently, they may become intractable for solving large-scale problems or be unsuitable for real-time embedded applications. Iterations of operator splitting methods are relatively simple and computationally inexpensive, which makes them suitable for these applications. We present OSQP, a general-purpose solver for quadratic programs based on operator splitting. The solver is very robust, is able to detect infeasible problems, and has been extensively tested on many problem instances from a wide variety of application areas. Our open-source C implementation has a small footprint, is library-free, and supports factorization caching and warm starting making it particularly efficient when solving parametrized problems arising in control, finance and machine learning.

CV:

Goran Banjac received the B.Sc. and M.Sc. degrees in electrical engineering from the Faculty of Electrical Engineering and Computing, University of Zagreb, Croatia, in 2011 and 2013, respectively. He was working as a research assistant at the Department of Control and Computer Engineering at the same University in 2013 and 2014. He is currently pursuing a D.Phil. degree in control engineering at the University of Oxford under the supervision of Prof. Paul Goulart. In 2016 he spent three months at Stanford University in the group of Prof. Stephen Boyd. His research interests include mathematical programming, optimal control, and numerical algorithms for high-speed and large-scale optimization.