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Martin Cooper

2 accepted papers

2022

Tractable Explanations for d-DNNF Classifiers

AAAI 2022technical

Compilation into propositional languages finds a growing number of practical uses, including in constraint programming, diagnosis and machine learning (ML), among others. One concrete example is the use of propositional languages as classifiers, and one natural question is how to explain the predict…

2020

Explaining Naive Bayes and Other Linear Classifiers with Polynomial Time and Delay

NeurIPS 2020spotlight

Recent work proposed the computation of so-called PI-explanations of Naive Bayes Classifiers (NBCs). PI-explanations are subset-minimal sets of feature-value pairs that are sufficient for the prediction, and have been computed with state-of-the-art exact algorithms that are worst-case exponential in…