Academic Bibliography

Search 200 years of publications by Ghent University researchers.

prof. dr. Tijl De Bie

Faculty of Engineering and Architecture > Department of Electronics and information systems

Work address: Technologiepark Zwijnaarde 122
9052 Zwijnaarde
Email: Tijl.DeBie@UGent.be
ORCID iD: 0000-0002-2692-7504

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- Journal Article
- A1
- open access
An empirical evaluation of network representation learning methods

Alexandru-Cristian Mara (UGent) , Jefrey Lijffijt (UGent) and Tijl De Bie (UGent)

(2023) BIG DATA.
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- Conference Paper
Mining Interesting Outlier Subgraphs in Attributed Graphs

Ahmad Mel (UGent) and Tijl De Bie (UGent)

(2022)
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- Conference Paper
Optimal transport of classifiers to fairness

Maarten Buyl (UGent) and Tijl De Bie (UGent)

(2022) NeurIPS 2022, 36th Conference on Neural Information Processing Systems, Proceedings. In Advances in Neural Information Processing Systems 35.
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- Miscellaneous
Inherent limitations of AI fairness

Maarten Buyl (UGent) and Tijl De Bie (UGent)

(2022)
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- Miscellaneous
A challenge-based survey of e-recruitment recommendation systems

Yoosof Mashayekhi (UGent) , Nan Li (UGent) , Bo Kang (UGent) , Jefrey Lijffijt (UGent) and Tijl De Bie (UGent)

(2022)
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A systematic evaluation of node embedding robustness

Alexandru-Cristian Mara (UGent) , Jefrey Lijffijt (UGent) , Stephan Günnemann and Tijl De Bie (UGent)

(2022) PROCEEDINGS OF MACHINE LEARNING RESEARCH. 198.
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Topologically regularized data embeddings

Robin Vandaele, Bo Kang (UGent) , Jefrey Lijffijt (UGent) , Tijl De Bie (UGent) and Yvan Saeys (UGent)

(2022) International Conference on Learning Representations (ICLR 2022), Proceedings.
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- Conference Paper
- C1
- open access
Embedding-based next song recommendation for playlists

Raphaël Romero (UGent) and Tijl De Bie (UGent)

(2022) ESANN 2022, 30th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Proceedings. p.503-508
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- Conference Paper
- C1
- open access
Graph-survival : a survival analysis framework for machine learning on temporal networks

Raphaël Romero (UGent) , Bo Kang (UGent) and Tijl De Bie (UGent)

(2022) ECML-PKDD 2022 PhD Forum, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Proceedings.
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- Conference Paper
- P1
- open access
The curse revisited : when are distances informative for the ground truth in noisy high-dimensional data?

Robin Vandaele, Bo Kang (UGent) , Tijl De Bie (UGent) and Yvan Saeys (UGent)

(2022) International Conference on Artificial Intelligence and Statistics, vol 151. In Proceedings of Machine Learning Research 151.

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