174 citations · 389 across the 26 of their papers we have counts for
4 papers · 1 filter
Mixture of Decision Trees for Interpretable Machine Learning
Simeon Brüggenjürgen, Nina Schaaf, Pascal Kerschke +1
This work introduces a novel interpretable machine learning method called Mixture of Decision Trees (MoDT). It constitutes a special case of the Mixture of Experts ensemble archite…
HPO X ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis
Lennart Schneider, Lennart Schäpermeier, Raphael Patrick Prager +3
Hyperparameter optimization (HPO) is a key component of machine learning models for achieving peak predictive performance. While numerous methods and algorithms for HPO have been p…
MOLE: Digging Tunnels Through Multimodal Multi-Objective Landscapes
Lennart Schäpermeier, Christian Grimme, Pascal Kerschke
Recent advances in the visualization of continuous multimodal multi-objective optimization (MMMOO) landscapes brought a new perspective to their search dynamics. Locally efficient…
A Collection of Deep Learning-based Feature-Free Approaches for Characterizing Single-Objective Continuous Fitness Landscapes
Moritz Vinzent Seiler, Raphael Patrick Prager, Pascal Kerschke +1
Exploratory Landscape Analysis is a powerful technique for numerically characterizing landscapes of single-objective continuous optimization problems. Landscape insights are crucia…