21 Publikationen
-
2024 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2988509Hinder, F., Vaquet, V., and Hammer, B. (2024). “A Remark on Concept Drift for Dependent Data” in Advances in Intelligent Data Analysis XXII. 22nd International Symposium on Intelligent Data Analysis, IDA 2024, Stockholm, Sweden, April 24–26, 2024, Proceedings, Part I, Miliou, I., Piatkowski, N., and Papapetrou, P. eds. Lecture Notes in Computer Science (Cham: Springer Nature Switzerland), 77-89.PUB | DOI
-
2024 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2987572Schroeder, S., Schulz, A., Hinder, F., and Hammer, B. (2024). “Semantic Properties of Cosine Based Bias Scores for Word Embeddings” in Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods. Vol. 1 (Setúbal, Portugal: SCITEPRESS - Science and Technology Publications), 160-168.PUB | DOI
-
2023 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2981289Hinder, F., Vaquet, V., Brinkrolf, J., and Hammer, B. (2023). Model-based explanations of concept drift. Neurocomputing:126640.PUB | DOI | Download (ext.) | WoS
-
2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982830Hinder, F., and Hammer, B. (2023). “Feature Selection for Concept Drift Detection” in ESANN 2023 Proceedings, Verleysen, M. ed.PUB
-
2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982167Hinder, F., Vaquet, V., Brinkrolf, J., and Hammer, B. (2023). “On the Hardness and Necessity of Supervised Concept Drift Detection” in Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods ICPRAM. Vol. 1, De Marsico, M., Sanniti di Baja, G., and Fred, A. eds. (Setúbal: SCITEPRESS - Science and Technology Publications), 164-175.PUB | DOI
-
2023 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2977934Hinder, F., Vaquet, V., Brinkrolf, J., and Hammer, B. (2023). “On the Change of Decision Boundary and Loss in Learning with Concept Drift” in Advances in Intelligent Data Analysis XXI. 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-la-Neuve, Belgium, April 12–14, 2023, Proceedings, Crémilleux, B., Hess, S., and Nijssen, S. eds. Lecture Notes in Computer Science, vol. 13876, (Cham: Springer ), 182-194.PUB | DOI
-
2022 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2962746Artelt, A., Hinder, F., Vaquet, V., Feldhans, R., and Hammer, B. (2022). Contrasting Explanations for Understanding and Regularizing Model Adaptations. Neural Processing Letters 55, 5273–5297.PUB | PDF | DOI | Download (ext.) | WoS
-
2022 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2984050Hinder, F., Vaquet, V., and Hammer, B. (2022). “Suitability of Different Metric Choices for Concept Drift Detection” in Advances in Intelligent Data Analysis XX. 20th International Symposium on Intelligent Data Analysis, IDA 2022, Rennes, France, April 20–22, 2022, Proceedings, Bouadi, T., Fromont, E., and Hüllermeier, E. eds. Lecture Notes in Computer Science (Cham: Springer International Publishing), 157-170.PUB | DOI
-
2022 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2966088Hinder, F., Vaquet, V., Brinkrolf, J., Artelt, A., and Hammer, B. (2022). “Localization of Concept Drift: Identifying the Drifting Datapoints” in 2022 International Joint Conference on Neural Networks (IJCNN) (IEEE), 1-9.PUB | DOI | Download (ext.)
-
2022 | Konferenzbeitrag | Angenommen | PUB-ID: 2964534Vaquet, V., Hinder, F., Brinkrolf, J., Menz, P., Seiffert, U., and 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.PUB
-
2022 | Kurzbeitrag Konferenz / Poster | PUB-ID: 2962861Hinder, F., Vaquet, V., Brinkrolf, J., Artelt, A., and Hammer, B. (2022).“Localization of Concept Drift: Identifying the Drifting Datapoints”.PUB
-
2021 | Konferenzbeitrag | PUB-ID: 2959428Hinder, F., Vaquet, V., Brinkrolf, J., and Hammer, B. (2021). Fast Non-Parametric Conditional Density Estimation using Moment Trees. IEEE Computational Intelligence Magazine.PUB
-
-
2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2960754Hinder, F., Brinkrolf, J., Vaquet, V., and Hammer, B. (2021). “A Shape-Based Method for Concept Drift Detection and Signal Denoising” in 2021 IEEE Symposium Series on Computational Intelligence (SSCI) Proceedings (Piscataway, NJ: IEEE), 01-08.PUB | DOI
-
2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2960755Hinder, F., Vaquet, V., Brinkrolf, J., and Hammer, B. (2021). “Fast Non-Parametric Conditional Density Estimation using Moment Trees” in 2021 IEEE Symposium Series on Computational Intelligence (SSCI) Proceedings (Piscataway, NJ: IEEE), 1-7.PUB | DOI
-
2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2957373Artelt, A., Hinder, F., Vaquet, V., Feldhans, R., and Hammer, B. (2021). “Contrastive Explanations for Explaining Model Adaptations” in Advances in Computational Intelligence. 16th International Work-Conference on Artificial Neural Networks, IWANN 2021, Virtual Event, June 16–18, 2021, Proceedings, Part I, Rojas, I., Joya, G., and Catala, A. eds. Lecture Notes in Computer Science (Cham: Springer ), 101-112.PUB | DOI
-
2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2962747Artelt, A., Vaquet, V., Velioglu, R., Hinder, F., Brinkrolf, J., Schilling, M., and Hammer, B. (2021). “Evaluating Robustness of Counterfactual Explanations” in 2021 IEEE Symposium Series on Computational Intelligence (SSCI) (Piscataway, NJ: IEEE), 01-09.PUB | DOI
-
2021 | Konferenzbeitrag | Angenommen | PUB-ID: 2956774Hinder, F., and Hammer, B. (Accepted). “Concept Drift Segmentation via Kolmogorov Trees” in Proceedings of the ESANN, 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Verleysen, M. ed.PUB
-
2020 | Konferenzbeitrag | PUB-ID: 2943260Schulz, A., Hinder, F., and Hammer, B. (2020). “DeepView: Visualizing Classification Boundaries of Deep Neural Networks as Scatter Plots Using Discriminative Dimensionality Reduction” in Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, {IJCAI-20}.PUB | DOI | Download (ext.) | arXiv
-
2020 | Konferenzbeitrag | PUB-ID: 2946488Hinder, F., Artelt, A., and Hammer, B. (2020). “Towards non-parametric drift detection via Dynamic Adapting Window Independence Drift Detection (DAWIDD)” in Proceedings of the 37th International Conference on Machine Learning.PUB | Download (ext.)
-
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