38 citations · 39 across the 3 of their papers we have counts for
6 papers
Computing the Shapley Value of Facts in Query Answering
Daniel Deutch, Nave Frost, Benny Kimelfeld +1
The Shapley value is a game-theoretic notion for wealth distribution that is nowadays extensively used to explain complex data-intensive computation, for instance, in network analy…
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…
Towards Deterministic Decomposable Circuits for Safe Queries
Mikaël Monet, Dan Olteanu
There exist two approaches for exact probabilistic inference of UCQs on tuple-independent databases. In the extensional approach, query evaluation is performed within a DBMS by exp…
Evaluating Datalog via Tree Automata and Cycluits
Antoine Amarilli, Pierre Bourhis, Mikaël Monet +1
We investigate parameterizations of both database instances and queries that make query evaluation fixed-parameter tractable in combined complexity. We show that clique-frontier-gu…