ERC Advanced Grant · 2024
Nonlinear Evolutions and Iterative Algorithms: Optimization and Control
Iterative algorithms (IA) stand as the very backbone of scientific computing. Traditional IA rely on convex optimization to guide the search for optima, severely limiting their scope to local solutions. Consequently, nonconvex problems are regarded as the ultimate challenge of global optimization. Solving them with convergence guarantees will lead to numerous scientific discoveries, such as finding new medications through optimization of the properties of molecules or enhancing materials for solar cells to accelerate advances in green technologies. The first goal of NEITALG is to design new, efficient, and scalable iterative algorithms that can provably solve relevant nonsmooth nonconvex…
From the public funding record at EU CORDIS. Describes the funded project, not the reviews below.