157 citations · 381 across the 18 of their papers we have counts for
3 papers · 1 filter
Foundations of Symbolic Languages for Model Interpretability
Marcelo Arenas, Daniel Baez, Pablo Barceló +2
Several queries and scores have recently been proposed to explain individual predictions over ML models. Given the need for flexible, reliable, and easy-to-apply interpretability m…
On the Complexity of SHAP-Score-Based Explanations: Tractability via Knowledge Compilation and Non-Approximability Results
Marcelo Arenas, Pablo Barceló, Leopoldo Bertossi +1
In Machine Learning, the -score is a version of the Shapley value that is used to explain the result of a learned model on a specific entity by assigning a score to…
The Tractability of SHAP-Score-Based Explanations over Deterministic and Decomposable Boolean Circuits
Marcelo Arenas, Pablo Barceló Leopoldo Bertossi, Mikaël Monet
Scores based on Shapley values are widely used for providing explanations to classification results over machine learning models. A prime example of this is the influential SHAP-sc…