38 citations · 80 across the 9 of their papers we have counts for
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cs.AI2020★ 38 cited
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…
cs.DB2020
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…