Hilde J. P. Weerts

Orcid: 0000-0002-2046-1299

According to our database1, Hilde J. P. Weerts authored at least 17 papers between 2017 and 2024.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoML.
J. Artif. Intell. Res., 2024

Subgroup Harm Assessor: Identifying Potential Fairness-Related Harms and Predictive Bias.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track and Demo Track, 2024

The Neutrality Fallacy: When Algorithmic Fairness Interventions are (Not) Positive Action.
Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024

Unlawful Proxy Discrimination: A Framework for Challenging Inherently Discriminatory Algorithms.
Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, 2024

2023
Fairlearn: Assessing and Improving Fairness of AI Systems.
J. Mach. Learn. Res., 2023

Look and You Will Find It: Fairness-Aware Data Collection through Active Learning.
Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2023), 2023

Algorithmic Unfairness through the Lens of EU Non-Discrimination Law: Or Why the Law is not a Decision Tree.
Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

Algorithmic Unfairness Through the Lens of EU Non-Discrimination Law.
Proceedings of the 2nd European Workshop on Algorithmic Fairness, 2023

Improving Recommender System Diversity with Variational Autoencoders.
Proceedings of the Advances in Bias and Fairness in Information Retrieval, 2023

2022
Does the End Justify the Means? On the Moral Justification of Fairness-Aware Machine Learning.
CoRR, 2022

Characterizing Data Scientists' Mental Models of Local Feature Importance.
Proceedings of the NordiCHI '22: Nordic Human-Computer Interaction Conference, Aarhus, Denmark, October 8, 2022

2021
An Introduction to Algorithmic Fairness.
CoRR, 2021

Teaching Responsible Machine Learning to Engineers.
Proceedings of the Second Teaching Machine Learning and Artificial Intelligence Workshop, 2021

2020
Importance of Tuning Hyperparameters of Machine Learning Algorithms.
CoRR, 2020

2019
Case-Based Reasoning for Assisting Domain Experts in Processing Fraud Alerts of Black-Box Machine Learning Models.
CoRR, 2019

A Human-Grounded Evaluation of SHAP for Alert Processing.
CoRR, 2019

2017
Have It Both Ways - From A/B Testing to A&B Testing with Exceptional Model Mining.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017


  Loading...