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03/29/2023
Local Interpretability of Random Forests for Multi-Target Regression
Multi-target regression is useful in a plethora of applications. Althoug...
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12/07/2022
Truthful Meta-Explanations for Local Interpretability of Machine Learning Models
Automated Machine Learning-based systems' integration into a wide range ...
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09/22/2022
Improving Attention-Based Interpretability of Text Classification Transformers
Transformers are widely used in NLP, where they consistently achieve sta...
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07/05/2022
Local Multi-Label Explanations for Random Forest
Multi-label classification is a challenging task, particularly in domain...
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04/29/2022
Local Explanation of Dimensionality Reduction
Dimensionality reduction (DR) is a popular method for preparing and anal...
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04/13/2021
LioNets: A Neural-Specific Local Interpretation Technique Exploiting Penultimate Layer Information
Artificial Intelligence (AI) has a tremendous impact on the unexpected g...
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04/13/2021
Conclusive Local Interpretation Rules for Random Forests
In critical situations involving discrimination, gender inequality, econ...
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03/31/2021
VisioRed: A Visualisation Tool for Interpretable Predictive Maintenance
The use of machine learning rapidly increases in high-risk scenarios whe...
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10/15/2020
Altruist: Argumentative Explanations through Local Interpretations of Predictive Models
Interpretable machine learning is an emerging field providing solutions ...
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06/11/2020
ETHOS: an Online Hate Speech Detection Dataset
Online hate speech is a newborn problem in our modern society which is g...
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11/20/2019
LionForests: Local Interpretation of Random Forests through Path Selection
Towards a future where machine learning systems will integrate into ever...
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06/15/2019