7 Publikationen
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2022 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2982135Jakob, J., Hasenjäger, M., and Hammer, B. (2022). “Reject Options for Incremental Regression Scenarios” in Artificial Neural Networks and Machine Learning – ICANN 2022. 31st International Conference on Artificial Neural Networks, Bristol, UK, September 6–9, 2022, Proceedings; Part IV, Pimenidis, E., Angelov, P., Jayne, C., Papaleonidas, A., and Aydin, M. eds. Lecture Notes in Computer Science (Cham: Springer Nature Switzerland), 248-259.PUB | DOI
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2022 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2969459Jakob, J., Artelt, A., Hasenjäger, M., and Hammer, B. (2022). “SAM-kNN Regressor for Online Learning in Water Distribution Networks” in Artificial Neural Networks and Machine Learning – ICANN 2022. 31st International Conference on Artificial Neural Networks, Bristol, UK, September 6–9, 2022, Proceedings, Part III, Pimenidis, E., Angelov, P., Jayne, C., Papaleonidas, A., and Aydin, M. eds. Lecture Notes in Computer Science, vol. 13531, (Cham: Springer Nature ), 752-762.PUB | DOI
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2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2939517Pfannschmidt, L., Jakob, J., Hinder, F., Biehl, M., Tino, P., and Hammer, B. (2020). Feature Relevance Determination for Ordinal Regression in the Context of Feature Redundancies and Privileged Information. Neurocomputing.PUB | DOI | Download (ext.) | WoS | arXiv
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2019 | Kurzbeitrag Konferenz / Poster | PUB-ID: 2935044Artelt, A., Jakob, J., and Vaquet, V. (2019).“Continuous online user authentication based on keystroke dynamics”. Presented at the Interdisciplinary College (IK), Günne/Möhnesee, Germany.PUB | Dateien verfügbar
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2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2933893Pfannschmidt, L., Jakob, J., Biehl, M., Tino, P., and Hammer, B. (2019). “Feature Relevance Bounds for Ordinal Regression” in Proceedings of the 27th European Symposium on Artificial Neural Networks (ESANN 2019), Verleysen, M. ed. ( Louvain-la-Neuve: i6doc).PUB | Download (ext.) | arXiv