23 citations · 40 across the 6 of their papers we have counts for
8 papers
SAT-based Encodings for Optimal Decision Trees with Explicit Paths
Mikoláš Janota, António Morgado
Decision trees play an important role both in Machine Learning and Knowledge Representation. They are attractive due to their immediate interpretability. In the spirit of Occam's r…
On Logic-Based Explainability with Partially Specified Inputs
Ramón Béjar, António Morgado, Jordi Planes +1
In the practical deployment of machine learning (ML) models, missing data represents a recurring challenge. Missing data is often addressed when training ML models. But missing dat…
Feature Necessity & Relevancy in ML Classifier Explanations
Xuanxiang Huang, Martin C. Cooper, Antonio Morgado +2
Given a machine learning (ML) model and a prediction, explanations can be defined as sets of features which are sufficient for the prediction. In some applications, and besides ask…
Model Based Diagnosis of Multiple Observations with Implicit Hitting Sets
Alexey Ignatiev, Antonio Morgado, Joao Marques-Silva
Model based diagnosis finds a growing range of practical applications, and significant performance-wise improvements have been achieved in recent years. Some of these improvements…
Horn Maximum Satisfiability: Reductions, Algorithms & Applications
Joao Marques-Silva, Alexey Ignatiev, Antonio Morgado
Recent years have witness remarkable performance improvements in maximum satisfiability (MaxSAT) solvers. In practice, MaxSAT algorithms often target the most generic MaxSAT formul…
On Tackling the Limits of Resolution in SAT Solving
Alexey Ignatiev, Antonio Morgado, Joao Marques-Silva
The practical success of Boolean Satisfiability (SAT) solvers stems from the CDCL (Conflict-Driven Clause Learning) approach to SAT solving. However, from a propositional proof com…