3 citations · 7 across the 11 of their papers we have counts for
4 papers · 2 filters
Evidential Rule Learning for Interpretable Classification with Abstention
Javier Fumanal-Idocin, Javier Andreu-Perez
Interpretable classification often requires more than accurate predictions for real-life deployment: models should be transparent about the evidence behind their decisions and abst…
Interpretable Fuzzy Rule-Based Regression Extension for Ex-Fuzzy Library
Cayan Deniz Kucuktopana, Javier Fumanal-Idocin, Richard Pitts +1
Machine learning models achieve high predictive accuracy in regression tasks, but their deployment in safety-critical and regulated domains requires interpretability. While fuzzy r…
Assessing Reliability of Symbol Detection in Concept Bottleneck Models
Javier Fumanal-Idocin, Javier Andreu-Perez
Concept Bottleneck Models (CBMs) are a relevant tool for explainable Artificial Intelligence because they make their predictions through human-interpretable symbols. However, high…
Hypernetworks for Dynamic Feature Selection
Javier Fumanal-Idocin, Raquel Fernandez-Peralta, Javier Andreu-Perez
Dynamic feature selection (DFS) is a machine learning framework in which features are acquired sequentially for individual samples under budget constraints. The exponential growth…