5 citations · 10 across the 5 of their papers we have counts for
5 papers · 1 filter
Formal Explanations for Neuro-Symbolic AI
Sushmita Paul, Jinqiang Yu, Jip J. Dekker +2
Despite the practical success of Artificial Intelligence (AI), current neural AI algorithms face two significant issues. First, the decisions made by neural architectures are often…
Anytime Approximate Formal Feature Attribution
Jinqiang Yu, Graham Farr, Alexey Ignatiev +1
Widespread use of artificial intelligence (AI) algorithms and machine learning (ML) models on the one hand and a number of crucial issues pertaining to them warrant the need for ex…
On Formal Feature Attribution and Its Approximation
Jinqiang Yu, Alexey Ignatiev, Peter J. Stuckey
Recent years have witnessed the widespread use of artificial intelligence (AI) algorithms and machine learning (ML) models. Despite their tremendous success, a number of vital prob…
Optimal Decision Lists using SAT
Jinqiang Yu, Alexey Ignatiev, Pierre Le Bodic +1
Decision lists are one of the most easily explainable machine learning models. Given the renewed emphasis on explainable machine learning decisions, this machine learning model is…
Computing Optimal Decision Sets with SAT
Jinqiang Yu, Alexey Ignatiev, Peter J. Stuckey +1
As machine learning is increasingly used to help make decisions, there is a demand for these decisions to be explainable. Arguably, the most explainable machine learning models use…