Large Scale Convex Optimization
Researchers: Pontus Giselsson, Mattias Fält, Martin Morin
Large-scale convex optimization problems appear naturally in many engineering fields such as machine learning, signal processing, image reconstruction, control, and bioinformatics. Many efficient algorithms exist that are specialized for a particular problem formulation. In this project, we are developing and analyzing general purpose algorithms that can solve all large-scale convex optimization problems. We are focusing on algorithm developement, theoretical algorithm analysis, as well as creation of software packages for user-friendly access to the developed methods.
Publications
Hamed Sadeghi: Efficient and Flexible First-Order Optimization Algorithms. PhD Thesis Department of Automatic Control, Lund University, Sweden, November 2022.
Hamed Sadeghi, Richard Pates, Anders Rantzer: "Anti-windup scheme for networked proportional-integral control". In 23rd International Symposium on Mathematical Theory of Networks and Systems, Hong Kong, China, July 2018.
2018-02-27