21 Publikationen
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2024 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2988509Hinder, F., Vaquet, V., & Hammer, B. (2024). A Remark on Concept Drift for Dependent Data. In I. Miliou, N. Piatkowski, & P. Papapetrou (Eds.), Lecture Notes in Computer Science. Advances in Intelligent Data Analysis XXII. 22nd International Symposium on Intelligent Data Analysis, IDA 2024, Stockholm, Sweden, April 24–26, 2024, Proceedings, Part I (pp. 77-89). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-58547-0_7
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2023 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2981289Hinder, F., Vaquet, V., Brinkrolf, J., & Hammer, B. (2023). Model-based explanations of concept drift. Neurocomputing, 126640. https://doi.org/10.1016/j.neucom.2023.126640
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2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982167Hinder, F., Vaquet, V., Brinkrolf, J., & Hammer, B. (2023). On the Hardness and Necessity of Supervised Concept Drift Detection. In M. De Marsico, G. Sanniti di Baja, & A. Fred (Eds.), Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods ICPRAM. Vol. 1 (pp. 164-175). Setúbal: SCITEPRESS - Science and Technology Publications. https://doi.org/10.5220/0011797500003411
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2023 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2977934Hinder, F., Vaquet, V., Brinkrolf, J., & Hammer, B. (2023). On the Change of Decision Boundary and Loss in Learning with Concept Drift. In B. Crémilleux, S. Hess, & S. Nijssen (Eds.), Lecture Notes in Computer Science: Vol. 13876. Advances in Intelligent Data Analysis XXI. 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-la-Neuve, Belgium, April 12–14, 2023, Proceedings (pp. 182-194). Cham: Springer . https://doi.org/10.1007/978-3-031-30047-9_15
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2022 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2962746Artelt, A., Hinder, F., Vaquet, V., Feldhans, R., & Hammer, B. (2022). Contrasting Explanations for Understanding and Regularizing Model Adaptations. Neural Processing Letters, 55, 5273–5297. https://doi.org/10.1007/s11063-022-10826-5
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2022 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2984050Hinder, F., Vaquet, V., & Hammer, B. (2022). Suitability of Different Metric Choices for Concept Drift Detection. In T. Bouadi, E. Fromont, & E. Hüllermeier (Eds.), Lecture Notes in Computer Science. Advances in Intelligent Data Analysis XX. 20th International Symposium on Intelligent Data Analysis, IDA 2022, Rennes, France, April 20–22, 2022, Proceedings (pp. 157-170). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-031-01333-1_13
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2022 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2966088Hinder, F., Vaquet, V., Brinkrolf, J., Artelt, A., & Hammer, B. (2022). Localization of Concept Drift: Identifying the Drifting Datapoints. 2022 International Joint Conference on Neural Networks (IJCNN), 1-9. IEEE. https://doi.org/10.1109/IJCNN55064.2022.9892374
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2022 | Konferenzbeitrag | Angenommen | PUB-ID: 2964534Vaquet, V., Hinder, F., Brinkrolf, J., Menz, P., Seiffert, U., & Hammer, B. (Accepted). Federated learning vector quantization for dealing with drift between nodes. Presented at the 30th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2022, Bruges.
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2022 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2962928Vaquet, V., Menz, P., Seiffert, U., & Hammer, B. (2022). Investigating Intensity and Transversal Drift in Hyperspectral Imaging Data. Neurocomputing. https://doi.org/10.1016/j.neucom.2022.07.011
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2022 | Kurzbeitrag Konferenz / Poster | PUB-ID: 2962861Hinder, F., Vaquet, V., Brinkrolf, J., Artelt, A., & Hammer, B. (2022). Localization of Concept Drift: Identifying the Drifting Datapoints. Presented at the
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2022 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2962650Vaquet, V., Artelt, A., Brinkrolf, J., & Hammer, B. (2022). Taking care of our drinking water: Dealing with Sensor Faults in Water Distribution Networks. Presented at the 31st International Conference on Artificial Neural Networks, Bristol.
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2021 | Konferenzbeitrag | PUB-ID: 2959428Hinder, F., Vaquet, V., Brinkrolf, J., & Hammer, B. (2021). Fast Non-Parametric Conditional Density Estimation using Moment Trees. IEEE Computational Intelligence Magazine
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2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2960687Vaquet, V., Hinder, F., Vaquet, J., Brinkrolf, J., & Hammer, B. (2021). Online Learning on Non-Stationary Data Streams for Image Recognition using Deep Embeddings. IEEE Symposium Series on Computational Intelligence, 1-7. https://doi.org/10.1109/SSCI50451.2021.9659903
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2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2960754Hinder, F., Brinkrolf, J., Vaquet, V., & Hammer, B. (2021). A Shape-Based Method for Concept Drift Detection and Signal Denoising. 2021 IEEE Symposium Series on Computational Intelligence (SSCI) Proceedings, 01-08. Piscataway, NJ: IEEE. https://doi.org/10.1109/SSCI50451.2021.9660111
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2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2960755Hinder, F., Vaquet, V., Brinkrolf, J., & Hammer, B. (2021). Fast Non-Parametric Conditional Density Estimation using Moment Trees. 2021 IEEE Symposium Series on Computational Intelligence (SSCI) Proceedings, 1-7. Piscataway, NJ: IEEE. https://doi.org/10.1109/SSCI50451.2021.9660031
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2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2960685Vaquet, V., Menz, P., Seiffert, U., & Hammer, B. (2021). Investigating Intensity and Transversal Drift in Hyperspectral Imaging Data. In M. Verleysen (Ed.), ESANN 2021 proceedings (pp. 47-52). Louvain-la-Neuve (Belgium): Ciaco - i6doc.com. https://doi.org/10.14428/esann/2021.ES2021-64
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2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2957373Artelt, A., Hinder, F., Vaquet, V., Feldhans, R., & Hammer, B. (2021). Contrastive Explanations for Explaining Model Adaptations. In I. Rojas, G. Joya, & A. Catala (Eds.), Lecture Notes in Computer Science. Advances in Computational Intelligence. 16th International Work-Conference on Artificial Neural Networks, IWANN 2021, Virtual Event, June 16–18, 2021, Proceedings, Part I (pp. 101-112). Cham: Springer . https://doi.org/10.1007/978-3-030-85030-2_9
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2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2962747Artelt, A., Vaquet, V., Velioglu, R., Hinder, F., Brinkrolf, J., Schilling, M., & Hammer, B. (2021). Evaluating Robustness of Counterfactual Explanations. 2021 IEEE Symposium Series on Computational Intelligence (SSCI), 01-09. Piscataway, NJ: IEEE. https://doi.org/10.1109/SSCI50451.2021.9660058
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2020 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2958328Vaquet, V., & Hammer, B. (2020). Balanced SAM-kNN: Online Learning with Heterogeneous Drift and Imbalanced Data. In I. Farkaš, P. Masulli, & S. Wermter (Eds.), Lecture Notes in Computer Science: Vol. 12397. Artificial Neural Networks and Machine Learning – ICANN 2020. 29th International Conference on Artificial Neural Networks, Bratislava, Slovakia, September 15–18, 2020, Proceedings, Part II (pp. 850-862). Cham: Springer. https://doi.org/10.1007/978-3-030-61616-8_68
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2019 | Kurzbeitrag Konferenz / Poster | PUB-ID: 2935044Artelt, A., Jakob, J., & Vaquet, V. (2019). Continuous online user authentication based on keystroke dynamics. Presented at the Interdisciplinary College (IK), Günne/Möhnesee, Germany.