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- Leibniz University HannoverDE89 papers
- Technische Informationsbibliothek (TIB)DE40 papers
- University of BonnDE13 papers
- GESIS - Leibniz Institute for the Social SciencesDE7 papers
- Indian Institute of Technology KharagpurIN6 papers
- University of KasselDE6 papers
- Delft University of TechnologyNL4 papers
- Freie Universität BerlinDE4 papers
- German Research Centre for Artificial IntelligenceDE4 papers
- Aalborg UniversityDK3 papers
- FIZ Karlsruhe – Leibniz Institute for Information InfrastructureDE3 papers
- FORTH Institute of Computer ScienceGR3 papers
9 papers · 2 filters
A survey on datasets for fairness-aware machine learning
Tai Le Quy, Arjun Roy, Vasileios Iosifidis +2
As decision-making increasingly relies on Machine Learning (ML) and (big) data, the issue of fairness in data-driven Artificial Intelligence (AI) systems is receiving increasing at…
XPROAX-Local explanations for text classification with progressive neighborhood approximation
Yi Cai, Arthur Zimek, Eirini Ntoutsi
The importance of the neighborhood for training a local surrogate model to approximate the local decision boundary of a black box classifier has been already highlighted in the lit…
LG4AV: Combining Language Models and Graph Neural Networks for Author Verification
Maximilian Stubbemann, Gerd Stumme
The automatic verification of document authorships is important in various settings. Researchers are for example judged and compared by the amount and impact of their publications…
Releasing Graph Neural Networks with Differential Privacy Guarantees
Iyiola E. Olatunji, Thorben Funke, Megha Khosla
With the increasing popularity of graph neural networks (GNNs) in several sensitive applications like healthcare and medicine, concerns have been raised over the privacy aspects of…
Mining Topological Dependencies of Recurrent Congestion in Road Networks
Nicolas Tempelmeier, Udo Feuerhake, Oskar Wage +1
The discovery of spatio-temporal dependencies within urban road networks that cause Recurrent Congestion (RC) patterns is crucial for numerous real-world applications, including ur…
Learnt Sparsification for Interpretable Graph Neural Networks
Mandeep Rathee, Zijian Zhang, Thorben Funke +2
Graph neural networks (GNNs) have achieved great success on various tasks and fields that require relational modeling. GNNs aggregate node features using the graph structure as ind…