11 citations · 28 across the 11 of their papers we have counts for
Showing 2024Show all
2 papers · 1 filter
cs.LG2024★ 1 cited
Optimal or Greedy Decision Trees? Revisiting their Objectives, Tuning, and Performance
Jacobus G. M. van der Linden, Daniël Vos, Mathijs M. de Weerdt +2
Recently there has been a surge of interest in optimal decision tree (ODT) methods that globally optimize accuracy directly, in contrast to traditional approaches that locally opti…
cs.LG2024★ 1 cited
Optimizing Interpretable Decision Tree Policies for Reinforcement Learning
Daniël Vos, Sicco Verwer
Reinforcement learning techniques leveraging deep learning have made tremendous progress in recent years. However, the complexity of neural networks prevents practitioners from und…