20 Publikationen

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  • [20]
    2023 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2981289
    F. Hinder, et al., “Model-based explanations of concept drift”, Neurocomputing, 2023, : 126640.
    PUB | DOI | Download (ext.) | WoS
     
  • [19]
    2023 | Konferenzbeitrag | Angenommen | PUB-ID: 2982899 OA
    V. Vaquet, J. Brinkrolf, and B. Hammer, “Robust Feature Selection and Robust Training to Cope with Hyperspectral Sensor Shifts”, Accepted.
    PUB | PDF
     
  • [18]
    2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982167
    F. Hinder, et al., “On the Hardness and Necessity of Supervised Concept Drift Detection”, Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods ICPRAM. Vol. 1, M. De Marsico, G. Sanniti di Baja, and A. Fred, eds., Setúbal: SCITEPRESS - Science and Technology Publications, 2023, pp.164-175.
    PUB | DOI
     
  • [17]
    2023 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2977934
    F. Hinder, et al., “On the Change of Decision Boundary and Loss in Learning with Concept Drift”, Advances in Intelligent Data Analysis XXI. 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-la-Neuve, Belgium, April 12–14, 2023, Proceedings, B. Crémilleux, S. Hess, and S. Nijssen, eds., Lecture Notes in Computer Science, vol. 13876, Cham: Springer , 2023, pp.182-194.
    PUB | DOI
     
  • [16]
    2022 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2962746 OA
    A. Artelt, et al., “Contrasting Explanations for Understanding and Regularizing Model Adaptations”, Neural Processing Letters, vol. 55, 2022, pp. 5273–5297.
    PUB | PDF | DOI | Download (ext.) | WoS
     
  • [15]
    2022 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2984050
    F. Hinder, V. Vaquet, and B. Hammer, “Suitability of Different Metric Choices for Concept Drift Detection”, Advances in Intelligent Data Analysis XX. 20th International Symposium on Intelligent Data Analysis, IDA 2022, Rennes, France, April 20–22, 2022, Proceedings, T. Bouadi, E. Fromont, and E. Hüllermeier, eds., Lecture Notes in Computer Science, Cham: Springer International Publishing, 2022, pp.157-170.
    PUB | DOI
     
  • [14]
    2022 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2966088
    F. Hinder, et al., “Localization of Concept Drift: Identifying the Drifting Datapoints”, 2022 International Joint Conference on Neural Networks (IJCNN), IEEE, 2022, pp.1-9.
    PUB | DOI | Download (ext.)
     
  • [13]
    2022 | Konferenzbeitrag | Angenommen | PUB-ID: 2964534
    V. Vaquet, et al., “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, Accepted.
    PUB
     
  • [12]
    2022 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2962928
    V. Vaquet, et al., “Investigating Intensity and Transversal Drift in Hyperspectral Imaging Data”, Neurocomputing, 2022.
    PUB | DOI | WoS
     
  • [11]
    2022 | Kurzbeitrag Konferenz / Poster | PUB-ID: 2962861
    F. Hinder, et al., “Localization of Concept Drift: Identifying the Drifting Datapoints”, 2022.
    PUB
     
  • [10]
    2022 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2962650 OA
    V. Vaquet, et al., “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, 2022.
    PUB | PDF
     
  • [9]
    2021 | Konferenzbeitrag | PUB-ID: 2959428
    F. Hinder, et al., “Fast Non-Parametric Conditional Density Estimation using Moment Trees”, IEEE Computational Intelligence Magazine, 2021.
    PUB
     
  • [8]
    2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2960687
    V. Vaquet, et al., “Online Learning on Non-Stationary Data Streams for Image Recognition using Deep Embeddings”, IEEE Symposium Series on Computational Intelligence, 2021, pp. 1-7.
    PUB | DOI
     
  • [7]
    2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2960754
    F. Hinder, et al., “A Shape-Based Method for Concept Drift Detection and Signal Denoising”, 2021 IEEE Symposium Series on Computational Intelligence (SSCI) Proceedings, Piscataway, NJ: IEEE, 2021, pp.01-08.
    PUB | DOI
     
  • [6]
    2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2960755
    F. Hinder, et al., “Fast Non-Parametric Conditional Density Estimation using Moment Trees”, 2021 IEEE Symposium Series on Computational Intelligence (SSCI) Proceedings, Piscataway, NJ: IEEE, 2021, pp.1-7.
    PUB | DOI
     
  • [5]
    2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2960685
    V. Vaquet, et al., “Investigating Intensity and Transversal Drift in Hyperspectral Imaging Data”, ESANN 2021 proceedings, M. Verleysen, ed., Louvain-la-Neuve (Belgium): Ciaco - i6doc.com, 2021, pp.47-52.
    PUB | DOI
     
  • [4]
    2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2957373
    A. Artelt, et al., “Contrastive Explanations for Explaining Model Adaptations”, Advances in Computational Intelligence. 16th International Work-Conference on Artificial Neural Networks, IWANN 2021, Virtual Event, June 16–18, 2021, Proceedings, Part I, I. Rojas, G. Joya, and A. Catala, eds., Lecture Notes in Computer Science, Cham: Springer , 2021, pp.101-112.
    PUB | DOI
     
  • [3]
    2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2962747
    A. Artelt, et al., “Evaluating Robustness of Counterfactual Explanations”, 2021 IEEE Symposium Series on Computational Intelligence (SSCI), Piscataway, NJ: IEEE, 2021, pp.01-09.
    PUB | DOI
     
  • [2]
    2020 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2958328
    V. Vaquet and B. Hammer, “Balanced SAM-kNN: Online Learning with Heterogeneous Drift and Imbalanced Data”, Artificial Neural Networks and Machine Learning – ICANN 2020. 29th International Conference on Artificial Neural Networks, Bratislava, Slovakia, September 15–18, 2020, Proceedings, Part II, I. Farkaš, P. Masulli, and S. Wermter, eds., Lecture Notes in Computer Science, vol. 12397, Cham: Springer, 2020, pp.850-862.
    PUB | DOI
     
  • [1]
    2019 | Kurzbeitrag Konferenz / Poster | PUB-ID: 2935044 OA
    A. Artelt, J. Jakob, and V. Vaquet, “Continuous online user authentication based on keystroke dynamics”, Presented at the Interdisciplinary College (IK), Günne/Möhnesee, Germany, 2019.
    PUB | Dateien verfügbar
     

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