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07/07/2023
On Formal Feature Attribution and Its Approximation
Recent years have witnessed the widespread use of artificial intelligenc...
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06/27/2023
Delivering Inflated Explanations
In the quest for Explainable Artificial Intelligence (XAI) one of the qu...
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12/12/2022
On Computing Probabilistic Abductive Explanations
The most widely studied explainable AI (XAI) approaches are unsound. Thi...
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06/20/2022
Eliminating The Impossible, Whatever Remains Must Be True
The rise of AI methods to make predictions and decisions has led to a pr...
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05/20/2022
On Tackling Explanation Redundancy in Decision Trees
Decision trees (DTs) epitomize the ideal of interpretability of machine ...
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05/19/2022
Provably Precise, Succinct and Efficient Explanations for Decision Trees
Decision trees (DTs) embody interpretable classifiers. DTs have been adv...
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07/04/2021
Efficient Explanations for Knowledge Compilation Languages
Knowledge compilation (KC) languages find a growing number of practical ...
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06/02/2021
On Efficiently Explaining Graph-Based Classifiers
Recent work has shown that not only decision trees (DTs) may not be inte...
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06/01/2021
Efficient Explanations With Relevant Sets
Recent work proposed δ-relevant inputs (or sets) as a probabilistic expl...
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06/01/2021
Explanations for Monotonic Classifiers
In many classification tasks there is a requirement of monotonicity. Con...
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05/14/2021
SAT-Based Rigorous Explanations for Decision Lists
Decision lists (DLs) find a wide range of uses for classification proble...
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02/03/2021
A Scalable Two Stage Approach to Computing Optimal Decision Sets
Machine learning (ML) is ubiquitous in modern life. Since it is being de...
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12/21/2020
On Relating 'Why?' and 'Why Not?' Explanations
Explanations of Machine Learning (ML) models often address a 'Why?' ques...
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10/21/2020
On Explaining Decision Trees
Decision trees (DTs) epitomize what have become to be known as interpret...
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10/19/2020
Optimal Decision Lists using SAT
Decision lists are one of the most easily explainable machine learning m...
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08/13/2020
Explaining Naive Bayes and Other Linear Classifiers with Polynomial Time and Delay
Recent work proposed the computation of so-called PI-explanations of Nai...
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07/29/2020
Computing Optimal Decision Sets with SAT
As machine learning is increasingly used to help make decisions, there i...
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07/04/2019
On Validating, Repairing and Refining Heuristic ML Explanations
Recent years have witnessed a fast-growing interest in computing explana...
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11/26/2018
Abduction-Based Explanations for Machine Learning Models
The growing range of applications of Machine Learning (ML) in a multitud...
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03/13/2018