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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
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- 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
34 papers · 1 filter
A Deep Latent Factor Graph Clustering with Fairness-Utility Trade-off Perspective
Siamak Ghodsi, Amjad Seyedi, Tai Le Quy +2
Fair graph clustering seeks partitions that respect network structure while maintaining proportional representation across sensitive groups, with applications spanning community de…
Spatially Constrained Transformer with Efficient Global Relation Modelling for Spatio-Temporal Prediction
Ashutosh Sao, Simon Gottschalk
Accurate spatio-temporal prediction is crucial for the sustainable development of smart cities. However, current approaches often struggle to capture important spatio-temporal rela…
Hyperparameter Importance Analysis for Multi-Objective AutoML
Daphne Theodorakopoulos, Frederic Stahl, Marius Lindauer
Hyperparameter optimization plays a pivotal role in enhancing the predictive performance and generalization capabilities of ML models. However, in many applications, we do not only…
Empowering machine learning models with contextual knowledge for enhancing the detection of eating disorders in social media posts
José Alberto Benítez-Andrades, María Teresa García-Ordás, Mayra Russo +3
Social networks are vital for information sharing, especially in the health sector for discussing diseases and treatments. These platforms, however, often feature posts as brief te…
Structure in Deep Reinforcement Learning: A Survey and Open Problems
Aditya Mohan, Amy Zhang, Marius Lindauer
Reinforcement Learning (RL), bolstered by the expressive capabilities of Deep Neural Networks (DNNs) for function approximation, has demonstrated considerable success in numerous a…
A review of clustering models in educational data science towards fairness-aware learning
Tai Le Quy, Gunnar Friege, Eirini Ntoutsi
Ensuring fairness is essential for every education system. Machine learning is increasingly supporting the education system and educational data science (EDS) domain, from decision…