PUB - Publikationen an der Universität Bielefeld

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• [11]
  

  2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982084

  Losing, V., Yoshikawa, T., Hasenjaeger, M., Hammer, B. & Wersing, H. (2019). Personalized Online Learning of Whole-Body Motion Classes using Multiple Inertial Measurement Units. 2019 International Conference on Robotics and Automation (ICRA) (S. 9530-9536). Gehalten auf der 2019 International Conference on Robotics and Automation (ICRA), IEEE. doi:10.1109/ICRA.2019.8794251.

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• [10]
  

  2019 | Bielefelder E-Dissertation | PUB-ID: 2936581

  Losing, V. (2019). Memory Models for Incremental Learning Architectures. Bielefeld: Universität Bielefeld. doi:10.4119/unibi/2936581.

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• [9]
  

  2018 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982088

  Losing, V., Wersing, H. & Hammer, B. (2018). Enhancing Very Fast Decision Trees with Local Split-Time Predictions. 2018 IEEE International Conference on Data Mining (ICDM) (S. 287-296). Gehalten auf der 2018 IEEE International Conference on Data Mining (ICDM), IEEE. doi:10.1109/ICDM.2018.00044.

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• [8]
  

  2018 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2917201

  Losing, V., Hammer, B. & Wersing, H. (2018). Tackling heterogeneous concept drift with the Self-Adjusting Memory (SAM). KNOWLEDGE AND INFORMATION SYSTEMS, 54(1), 171-201. Springer London Ltd. doi:10.1007/s10115-017-1137-y.

  PUB | DOI | WoS
   
• [7]
  

  2018 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2914730

  Losing, V., Hammer, B. & Wersing, H. (2018). Incremental on-line learning: A review and comparison of state of the art algorithms. Neurocomputing, 275, 1261-1274. Elsevier BV. doi:10.1016/j.neucom.2017.06.084.

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• [6]
  

  2017 | Konferenzbeitrag | PUB-ID: 2914734

  Losing, V., Hammer, B. & Wersing, H. (2017). Self-Adjusting Memory: How to Deal with Diverse Drift Types. Gehalten auf der International Joint Conference on Artificial Intelligence (IJCAI) 2017, International Joint Conferences on Artificial Intelligence. doi:10.24963/ijcai.2017/690.

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• [5]
  

  2017 | Konferenzbeitrag | PUB-ID: 2914732

  Losing, V., Hammer, B. & Wersing, H. (2017). Personalized Maneuver Prediction at Intersections. Gehalten auf der IEEE Intelligent Transportation Systems Conference 2017.

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• [4]
  

  2016 | Konferenzbeitrag | PUB-ID: 2907624

  Losing, V., Hammer, B. & Wersing, H. (2016). Choosing the Best Algorithm for an Incremental On-line Learning Task. Gehalten auf der European Symposium on Artificial Neural Networks.

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• [3]
  

  2016 | Konferenzbeitrag | PUB-ID: 2908455

  Losing, V., Hammer, B. & Wersing, H. (2016). Dedicated Memory Models for Continual Learning in the Presence of Concept Drift. Gehalten auf der Continual Learning Workshop of the Thirtieth Annual Conference on Neural Information Processing Systems (NIPS).

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• [2]
  

  2016 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2907622

  Losing, V., Hammer, B. & Wersing, H. (2016). KNN Classifier with Self Adjusting Memory for Heterogeneous Concept Drift. 2016 IEEE 16th International Conference on Data Mining (ICDM) (S. 291-300). Gehalten auf der International Conference On Data Mining, Piscataway, NJ: IEEE. doi:10.1109/ICDM.2016.0040.

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• [1]
  

  2015 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2776021

  Losing, V., Hammer, B. & Wersing, H. (2015). Interactive Online Learning for Obstacle Classification on a Mobile Robot. Gehalten auf der International Joint Conference on Neural Networks, IEEE. doi:10.1109/IJCNN.2015.7280610.

  PUB | PDF | DOI