Publicaties
A multilevel Monte Carlo method for asymptotic-preserving particle schemes in the diffusive limit KU Leuven
On the nonexistence and rigidity for hypersurfaces of the homogeneous nearly Kahler S-3 x S-3 KU Leuven
Two‐level preconditioning for Ridge Regression KU Leuven
Solving linear systems is often the computational bottleneck in real‐life problems. Iterative solvers are the only option due to the complexity of direct algorithms or because the system matrix is not explicitly known. Here, we develop a two‐level preconditioner for regularized least squares linear systems involving a feature or data matrix. Variants of this linear system may appear in machine learning applications, such as ridge regression, ...
Generating set search using simplex gradients for bound-constrained black-box optimization KU Leuven
The optimization problems arising in modern engineering practice are increasingly simulation-based, characterized by extreme types of nonsmoothness, the inaccessibility of derivatives, and high computational expense. While generating set searches (GSS) generally offer a satisfying level of robustness and convergence to stationary points, the convergence rates may be slow. In order to accelerate the solution process without sacrificing ...