Continuous optimization plays a central role in modern machine learning. Every learning process requires solving a high-dimensional minimization problem. The faster we solve it, the fewer resources (e.g., energy, time, or money) we waste.
Current state-of-the-art algorithms include some heuristics and often require a lot of tuning. The theoretical justification of these heuristics and the developing of new, more efficient algorithms is the main focus of our group.
This page is about WASP Mathematics. For more information about the entire WASP at LiU, go up one level in the menu to WASP - Wallenberg AI, Autonomous Systems and Software Program. You will also find a contact list of all WASP researchers at LiU divided by department there.
