4 citations · 4 across the 11 of their papers we have counts for
3 papers · 1 filter
Multi-Objective Optimization with Desirability and Morris-Mitchell Criterion
Thomas Bartz-Beielstein, Eva Bartz, Alexander Hinterleitner +2
Industrial experimental designs frequently lack optimal space-filling properties, rendering them unrepresentative. This study presents a comprehensive methodology to refine existin…
Tuning for Trustworthiness -- Balancing Performance and Explanation Consistency in Neural Network Optimization
Alexander Hinterleitner, Thomas Bartz-Beielstein
Despite the growing interest in Explainable Artificial Intelligence (XAI), explainability is rarely considered during hyperparameter tuning or neural architecture optimization, whe…
Multi-Objective Optimization and Hyperparameter Tuning With Desirability Functions
Thomas Bartz-Beielstein
The desirability-function approach is a widely adopted method for optimizing multiple-response processes. Kuhn (2016) implemented the packages desirability and desirability2 in the…