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Hilde J. P. Weerts

Hilde Jacoba Petronella Weerts

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2020 – today

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2023
[i8]
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  - journals/corr/abs-2303-08485
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Hilde J. P. Weerts, Florian Pfisterer, Matthias Feurer, Katharina Eggensperger, Edward Bergman, Noor H. Awad, Joaquin Vanschoren, Mykola Pechenizkiy, Bernd Bischl, Frank Hutter:
Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoML. CoRR abs/2303.08485 (2023)
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  - journals/corr/abs-2303-16626
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Hilde J. P. Weerts, Miroslav Dudík, Richard Edgar, Adrin Jalali, Roman Lutz, Michael Madaio:
Fairlearn: Assessing and Improving Fairness of AI Systems. CoRR abs/2303.16626 (2023)
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  - journals/corr/abs-2305-13938
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Hilde J. P. Weerts, Raphaële Xenidis, Fabien Tarissan, Henrik Palmer Olsen, Mykola Pechenizkiy:
Algorithmic Unfairness through the Lens of EU Non-Discrimination Law: Or Why the Law is not a Decision Tree. CoRR abs/2305.13938 (2023)
2022
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  - conf/nordichi/CollarisWMWP22
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Dennis Collaris, Hilde J. P. Weerts, Daphne Miedema, Jarke J. van Wijk, Mykola Pechenizkiy:
Characterizing Data Scientists' Mental Models of Local Feature Importance. NordiCHI 2022: 9:1-9:12
[i5]
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  - journals/corr/abs-2202-08536
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Hilde J. P. Weerts, Lambèr Royakkers, Mykola Pechenizkiy:
Does the End Justify the Means? On the Moral Justification of Fairness-Aware Machine Learning. CoRR abs/2202.08536 (2022)
2021
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Hilde Jacoba Petronella Weerts, Mykola Pechenizkiy:
Teaching Responsible Machine Learning to Engineers. Teaching ML 2021: 40-45
[i4]
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  - journals/corr/abs-2105-05595
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Hilde J. P. Weerts:
An Introduction to Algorithmic Fairness. CoRR abs/2105.05595 (2021)
2020
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  - journals/corr/abs-2007-07588
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Hilde J. P. Weerts, Andreas C. Mueller, Joaquin Vanschoren:
Importance of Tuning Hyperparameters of Machine Learning Algorithms. CoRR abs/2007.07588 (2020)

2010 – 2019

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2019
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  - journals/corr/abs-1907-03324
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Hilde J. P. Weerts, Werner van Ipenburg, Mykola Pechenizkiy:
A Human-Grounded Evaluation of SHAP for Alert Processing. CoRR abs/1907.03324 (2019)
[i1]
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  - journals/corr/abs-1907-03334
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Hilde J. P. Weerts, Werner van Ipenburg, Mykola Pechenizkiy:
Case-Based Reasoning for Assisting Domain Experts in Processing Fraud Alerts of Black-Box Machine Learning Models. CoRR abs/1907.03334 (2019)
2017
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  - conf/pkdd/DuivesteijnFPPW17
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Wouter Duivesteijn, Tara Farzami, Thijs Putman, Evertjan Peer, Hilde J. P. Weerts, Jasper N. Adegeest, Gerson Foks, Mykola Pechenizkiy:
Have It Both Ways - From A/B Testing to A&B Testing with Exceptional Model Mining. ECML/PKDD (3) 2017: 114-126

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