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09/01/2023
Declarative Reasoning on Explanations Using Constraint Logic Programming
Explaining opaque Machine Learning (ML) models is an increasingly releva...
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07/28/2023
The Initial Screening Order Problem
In this paper we present the initial screening order problem, a crucial ...
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05/29/2023
Reason to explain: Interactive contrastive explanations (REASONX)
Many high-performing machine learning models are not interpretable. As t...
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03/14/2023
Demographic Parity Inspector: Fairness Audits via the Explanation Space
Even if deployed with the best intentions, machine learning methods can ...
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02/27/2023
Domain Adaptive Decision Trees: Implications for Accuracy and Fairness
In uses of pre-trained machine learning models, it is a known issue that...
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02/23/2023
Counterfactual Situation Testing: Uncovering Discrimination under Fairness given the Difference
We present counterfactual situation testing (CST), a causal data mining ...
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10/19/2022
AUC-based Selective Classification
Selective classification (or classification with a reject option) pairs ...
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01/27/2022
Fairness implications of encoding protected categorical attributes
Protected attributes are often presented as categorical features that ne...
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01/24/2021
Estimating the Total Volume of Queries to a Search Engine
We study the problem of estimating the total number of searches (volume)...
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04/10/2020
Give more data, awareness and control to individual citizens, and they will help COVID-19 containment
The rapid dynamics of COVID-19 calls for quick and effective tracking of...
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01/14/2020
Bias in Data-driven AI Systems – An Introductory Survey
AI-based systems are widely employed nowadays to make decisions that hav...
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10/22/2018
Assessing the Stability of Interpretable Models
Interpretable classification models are built with the purpose of provid...
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06/26/2018
Open the Black Box Data-Driven Explanation of Black Box Decision Systems
Black box systems for automated decision making, often based on machine ...
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05/28/2018