38 citations · 99 across the 20 of their papers we have counts for
3 papers · 1 filter
Model Interpretability through the Lens of Computational Complexity
Pablo Barceló, Mikaël Monet, Jorge Pérez +1
In spite of several claims stating that some models are more interpretable than others -- e.g., "linear models are more interpretable than deep neural networks" -- we still lack a…
The Complexity of Counting Problems over Incomplete Databases
Marcelo Arenas, Pablo Barceló, Mikaël Monet
We study the complexity of various fundamental counting problems that arise in the context of incomplete databases, i.e., relational databases that can contain unknown values in th…
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…