Interactive Pareto navigation for deep multi-task learning
A.C. Amakor, K. Sonntag, S. Peitz, in: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2026, pp. 652–668.
Download (ext.)
Conference Paper
| English
Department
Keywords
Publishing Year
Proceedings Title
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD)
Page
652-668
LibreCat-ID
Cite this
Amakor AC, Sonntag K, Peitz S. Interactive Pareto navigation for deep multi-task learning. In: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD). ; 2026:652-668. doi:10.1007/978-3-032-37667-1_37
Amakor, A. C., Sonntag, K., & Peitz, S. (2026). Interactive Pareto navigation for deep multi-task learning. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 652–668. https://doi.org/10.1007/978-3-032-37667-1_37
@inproceedings{Amakor_Sonntag_Peitz_2026, title={Interactive Pareto navigation for deep multi-task learning}, DOI={10.1007/978-3-032-37667-1_37}, booktitle={European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD)}, author={Amakor, Augustina Chidinma and Sonntag, Konstantin and Peitz, Sebastian}, year={2026}, pages={652–668} }
Amakor, Augustina Chidinma, Konstantin Sonntag, and Sebastian Peitz. “Interactive Pareto Navigation for Deep Multi-Task Learning.” In European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 652–68, 2026. https://doi.org/10.1007/978-3-032-37667-1_37.
A. C. Amakor, K. Sonntag, and S. Peitz, “Interactive Pareto navigation for deep multi-task learning,” in European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2026, pp. 652–668, doi: 10.1007/978-3-032-37667-1_37.
Amakor, Augustina Chidinma, et al. “Interactive Pareto Navigation for Deep Multi-Task Learning.” European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2026, pp. 652–68, doi:10.1007/978-3-032-37667-1_37.
All files available under the following license(s):
Copyright Statement:
This Item is protected by copyright and/or related rights. [...]
Link(s) to Main File(s)
Access Level
Closed Access
Google Scholar