3 citations · 7 across the 11 of their papers we have counts for
3 papers · 2 filters
A Fast Interpretable Fuzzy Tree Learner
Javier Fumanal-Idocin, Raquel Fernandez-Peralta, Javier Andreu-Perez
Fuzzy rule-based systems have been mostly used in interpretable decision-making because of their interpretable linguistic rules. However, interpretability requires both sensible li…
Model-Agnostic Dynamic Feature Selection with Uncertainty Quantification
Javier Fumanal-Idocin, Raquel Fernandez-Peralta, Javier Andreu-Perez
Dynamic feature selection (DFS) addresses budget constraints in decision-making by sequentially acquiring features for each instance, making it appealing for resource-limited scena…
Compact Rule-Based Classifier Learning via Gradient Descent
Javier Fumanal-Idocin, Raquel Fernandez-Peralta, Javier Andreu-Perez
Rule-based models are essential for high-stakes decision-making due to their transparency and interpretability, but their discrete nature creates challenges for optimization and sc…