PUB - Publikationen an der Universität Bielefeld

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• [21]
  

  2024 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2988509

  Hinder, F.; Vaquet, V.; Hammer, B. (2024): A Remark on Concept Drift for Dependent Data. In: Ioanna Miliou; Nico Piatkowski; Panagiotis Papapetrou (Hrsg.): Advances in Intelligent Data Analysis XXII. 22nd International Symposium on Intelligent Data Analysis, IDA 2024, Stockholm, Sweden, April 24–26, 2024, Proceedings, Part I. Cham: Springer Nature Switzerland. (Lecture Notes in Computer Science, ). S. 77-89.

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• [20]
  

  2024 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2987572

  Schroeder, S.; Schulz, A.; Hinder, F.; 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. S. 160-168.

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• [19]
  

  2023 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2981289

  Hinder, F.; Vaquet, V.; Brinkrolf, J.; Hammer, B. (2023): Model-based explanations of concept drift Neurocomputing,126640

  PUB | DOI | Download (ext.) | WoS
   
• [18]
  

  2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982830

  Hinder, F.; Hammer, B. (2023): Feature Selection for Concept Drift Detection. In: Michel Verleysen (Hrsg.): ESANN 2023 Proceedings.

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• [17]
  

  2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982167

  Hinder, F.; Vaquet, V.; Brinkrolf, J.; Hammer, B. (2023): On the Hardness and Necessity of Supervised Concept Drift Detection. In: Maria De Marsico; Gabriella Sanniti di Baja; Ana Fred (Hrsg.): Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods ICPRAM. Vol. 1. Setúbal: SCITEPRESS - Science and Technology Publications. S. 164-175.

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• [16]
  

  2023 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2977934

  Hinder, F.; Vaquet, V.; Brinkrolf, J.; Hammer, B. (2023): On the Change of Decision Boundary and Loss in Learning with Concept Drift. In: Bruno Crémilleux; Sibylle Hess; Siegfried Nijssen (Hrsg.): Advances in Intelligent Data Analysis XXI. 21st International Symposium on Intelligent Data Analysis, IDA 2023, Louvain-la-Neuve, Belgium, April 12–14, 2023, Proceedings. Cham: Springer . (Lecture Notes in Computer Science, 13876). S. 182-194.

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• [15]
  

  2022 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2962746

  Artelt, A.; Hinder, F.; Vaquet, V.; Feldhans, R.; Hammer, B. (2022): Contrasting Explanations for Understanding and Regularizing Model Adaptations Neural Processing Letters,55: 5273–5297.

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• [14]
  

  2022 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2984050

  Hinder, F.; Vaquet, V.; Hammer, B. (2022): Suitability of Different Metric Choices for Concept Drift Detection. In: Tassadit Bouadi; Elisa Fromont; Eyke Hüllermeier (Hrsg.): Advances in Intelligent Data Analysis XX. 20th International Symposium on Intelligent Data Analysis, IDA 2022, Rennes, France, April 20–22, 2022, Proceedings. Cham: Springer International Publishing. (Lecture Notes in Computer Science, ). S. 157-170.

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• [13]
  

  2022 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2966088

  Hinder, F.; Vaquet, V.; Brinkrolf, J.; Artelt, A.; Hammer, B. (2022): Localization of Concept Drift: Identifying the Drifting Datapoints. In: 2022 International Joint Conference on Neural Networks (IJCNN). IEEE. S. 1-9.

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• [12]
  

  2022 | Konferenzbeitrag | Angenommen | PUB-ID: 2964534

  Vaquet, V.; Hinder, F.; Brinkrolf, J.; Menz, P.; Seiffert, U.; Hammer, B. (Accepted): Federated learning vector quantization for dealing with drift between nodes.

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• [11]
  

  2022 | Kurzbeitrag Konferenz / Poster | PUB-ID: 2962861

  Hinder, F.; Vaquet, V.; Brinkrolf, J.; Artelt, A.; Hammer, B. (2022): Localization of Concept Drift: Identifying the Drifting Datapoints.

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• [10]
  

  2021 | Konferenzbeitrag | PUB-ID: 2959428

  Hinder, 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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• [9]
  

  2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2960687

  Vaquet, V.; Hinder, F.; Vaquet, J.; Brinkrolf, J.; Hammer, B. (2021): Online Learning on Non-Stationary Data Streams for Image Recognition using Deep Embeddings, In: IEEE (Hrsg.), IEEE Symposium Series on Computational Intelligence, 1-7.

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• [8]
  

  2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2960754

  Hinder, F.; Brinkrolf, J.; Vaquet, V.; 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. S. 01-08.

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• [7]
  

  2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2960755

  Hinder, F.; Vaquet, V.; Brinkrolf, J.; 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. S. 1-7.

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• [6]
  

  2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2957373

  Artelt, A.; Hinder, F.; Vaquet, V.; Feldhans, R.; Hammer, B. (2021): Contrastive Explanations for Explaining Model Adaptations. In: Ignacio Rojas; Gonzalo Joya; Andreu Catala (Hrsg.): Advances in Computational Intelligence. 16th International Work-Conference on Artificial Neural Networks, IWANN 2021, Virtual Event, June 16–18, 2021, Proceedings, Part I. Cham: Springer . (Lecture Notes in Computer Science, ). S. 101-112.

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• [5]
  

  2021 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2962747

  Artelt, A.; Vaquet, V.; Velioglu, R.; Hinder, F.; Brinkrolf, J.; Schilling, M.; Hammer, B. (2021): Evaluating Robustness of Counterfactual Explanations. In: 2021 IEEE Symposium Series on Computational Intelligence (SSCI). Piscataway, NJ: IEEE. S. 01-09.

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• [4]
  

  2021 | Konferenzbeitrag | Angenommen | PUB-ID: 2956774

  Hinder, F.; Hammer, B. (Accepted): Concept Drift Segmentation via Kolmogorov Trees. In: Michel Verleysen (Hrsg.): Proceedings of the ESANN, 29th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning.

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• [3]
  

  2020 | Konferenzbeitrag | PUB-ID: 2943260

  Schulz, A.; Hinder, F.; 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
   
• [2]
  

  2020 | Konferenzbeitrag | PUB-ID: 2946488

  Hinder, F.; Artelt, A.; 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.

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• [1]
  

  2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2939517

  Pfannschmidt, L.; Jakob, J.; Hinder, F.; Biehl, M.; Tino, P.; 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