ExplAIner is a layered first-order logic that expresses major XAI explanation queries over Boolean models with evaluation in the Boolean hierarchy and computation in FP^NP.
1995.Foundations of Databases
4 Pith papers cite this work. Polarity classification is still indexing.
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Gradient-guided rewiring of foreign-key edges in relational databases degrades GNN predictions on regression tasks while preserving schema integrity constraints.
SPARQL, multiset Datalog, and multiset relational algebra are expressively equivalent for AND, UNION, FILTER, EXCEPT, and SELECT.
The paper introduces GO-FDs and graph-native normal forms that push redundancy out of labeled property graphs, covering not just node properties but also edge properties.
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ExplAIner: A Declarative Query Language for Explaining Classification Models
ExplAIner is a layered first-order logic that expresses major XAI explanation queries over Boolean models with evaluation in the Boolean hierarchy and computation in FP^NP.