3 papers
cs.LG2026
Interactive Pareto navigation for deep multi-task learning
Augustina C. Amakor, Konstantin Sonntag, Sebastian Peitz
In multi-task learning, handling an increasing number of objectives can quickly become challenging, both in terms of the computational resources and the decision maker's capacity t…
math.OC2024
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…
cs.LG2023
A multiobjective continuation method to compute the regularization path of deep neural networks
Augustina C. Amakor, Konstantin Sonntag, Sebastian Peitz
Sparsity is a highly desired feature in deep neural networks (DNNs) since it ensures numerical efficiency, improves the interpretability of models (due to the smaller number of rel…