On tackling explanation redundancy in decision trees
Decision trees (DTs) epitomize the ideal of interpretability of machine learning (ML) models.
The interpretability of decision trees motivates explainability approaches by so-called …
The interpretability of decision trees motivates explainability approaches by so-called …
Conflict-driven clause learning SAT solvers
One of the most important paradigm shifts in the use of SAT solvers for solving industrial
problems has been the introduction of clause learning. Clause learning entails adding a …
problems has been the introduction of clause learning. Clause learning entails adding a …
Logic-based explainability in machine learning
J Marques-Silva - … Knowledge: 18th International Summer School 2022 …, 2023 - Springer
The last decade witnessed an ever-increasing stream of successes in Machine Learning
(ML). These successes offer clear evidence that ML is bound to become pervasive in a wide …
(ML). These successes offer clear evidence that ML is bound to become pervasive in a wide …
SAT-based rigorous explanations for decision lists
A Ignatiev, J Marques-Silva - … and Applications of Satisfiability Testing–SAT …, 2021 - Springer
Decision lists (DLs) find a wide range of uses for classification problems in Machine
Learning (ML), being implemented in anumber of ML frameworks. DLs are often perceived …
Learning (ML), being implemented in anumber of ML frameworks. DLs are often perceived …
Smallest MUS extraction with minimal hitting set dualization
Minimal explanations of infeasibility are of great interest in many domains. In propositional
logic, these are referred to as Minimal Unsatisfiable Subsets (MUSes). An unsatisfiable …
logic, these are referred to as Minimal Unsatisfiable Subsets (MUSes). An unsatisfiable …
Minimal sets over monotone predicates in boolean formulae
The importance and impact of the Boolean satisfiability (SAT) problem in many practical
settings is well-known. Besides SAT, a number of computational problems related with …
settings is well-known. Besides SAT, a number of computational problems related with …
Eliminating the impossible, whatever remains must be true: On extracting and applying background knowledge in the context of formal explanations
The rise of AI methods to make predictions and decisions has led to a pressing need for
more explainable artificial intelligence (XAI) methods. One common approach for XAI is to …
more explainable artificial intelligence (XAI) methods. One common approach for XAI is to …
Core-guided minimal correction set and core enumeration
N Narodytska, N Bjørner… - … Joint Conference on …, 2018 - upcommons.upc.edu
A set of constraints is unsatisfiable if there is no solution that satisfies these constraints. To
analyse unsatisfiable problems, the user needs to understand where inconsistencies come …
analyse unsatisfiable problems, the user needs to understand where inconsistencies come …
Eliminating the impossible, whatever remains must be true
The rise of AI methods to make predictions and decisions has led to a pressing need for
more explainable artificial intelligence (XAI) methods. One common approach for XAI is to …
more explainable artificial intelligence (XAI) methods. One common approach for XAI is to …
[HTML][HTML] Understanding the complexity of axiom pinpointing in lightweight description logics
R Penaloza, B Sertkaya - Artificial Intelligence, 2017 - Elsevier
Lightweight description logics are knowledge representation formalisms characterised by
the low complexity of their standard reasoning tasks. They have been successfully employed …
the low complexity of their standard reasoning tasks. They have been successfully employed …