9 citations · 10 across the 4 of their papers we have counts for
4 papers
Surrogate-assisted multi-objective design of complex multibody systems
Augustina C. Amakor, Manuel B. Berkemeier, Meike Wohlleben +2
The optimization of large-scale multibody systems is a numerically challenging task, in particular when considering multiple conflicting criteria at the same time. In this situatio…
Multi-Objective Optimization for Sparse Deep Multi-Task Learning
S. S. Hotegni, M. Berkemeier, S. Peitz
Different conflicting optimization criteria arise naturally in various Deep Learning scenarios. These can address different main tasks (i.e., in the setting of Multi-Task Learning)…
Multi-Objective Trust-Region Filter Method for Nonlinear Constraints using Inexact Gradients
Manuel Berkemeier, Sebastian Peitz
In this article, we build on previous work to present an optimization algorithm for nonlinearly constrained multi-objective optimization problems. The algorithm combines a surrogat…
Derivative-Free Multiobjective Trust Region Descent Method Using Radial Basis Function Surrogate Models
Manuel Berkemeier, Sebastian Peitz
We present a flexible trust region descend algorithm for unconstrained and convexly constrained multiobjective optimization problems. It is targeted at heterogeneous and expensive…