7 Publikationen
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2022 | Bielefelder E-Dissertation | PUB-ID: 2962486Limberg, C. (2022). Competence Modeling for Human-Robot Cooperation. Bielefeld: Universität Bielefeld. https://doi.org/10.4119/unibi/2962486PUB | PDF | DOI
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2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2950092Limberg, C., Wersing, H., & Ritter, H. (2020). Beyond Cross-Validation—Accuracy Estimation for Incremental and Active Learning Models. Machine Learning and Knowledge Extraction, 2(3), 327-346. https://doi.org/10.3390/make2030018PUB | DOI | WoS
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2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2950093Limberg, C., Wersing, H., & Ritter, H. (2020). Accuracy Estimation for an Incrementally Learning Cooperative Inventory Assistant Robot. In H. Yang, K. Pasupa, A. C. - S. Leung, J. T. Kwok, J. H. Chan, & I. King (Eds.), Lecture Notes in Computer Science: Vol. 12533. Neural Information Processing. 27th International Conference, ICONIP 2020, Bangkok, Thailand, November 23–27, 2020, Proceedings, Part II (pp. 738-749). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-63833-7_62PUB | DOI
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2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2950094Limberg, C., Göpfert, J. P., Wersing, H., & Ritter, H. (2020). Prototype-Based Online Learning on Homogeneously Labeled Streaming 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. 204-213). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-61616-8_17PUB | DOI
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2019 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2939051Limberg, C., Krieger, K., Wersing, H., & Ritter, H. (2019). Active Learning for Image Recognition Using a Visualization-Based User Interface. In I. V. Tetko, V. Kůrková, P. Karpov, & F. Theis (Eds.), Lecture Notes in Computer Science: Vol. 11728. Artificial Neural Networks and Machine Learning – ICANN 2019: Deep Learning (pp. 495-506). Cham: Springer. doi:10.1007/978-3-030-30484-3_40PUB | PDF | DOI
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2018 | Sammelwerksbeitrag | Veröffentlicht | PUB-ID: 2939050Limberg, C., Wersing, H., & Ritter, H. (2018). Improving Active Learning by Avoiding Ambiguous Samples. In V. Kůrková, Y. Manolopoulos, B. Hammer, L. Iliadis, & I. Maglogiannis (Eds.), Lecture Notes in Computer Science: Vol. 11139. Artificial Neural Networks and Machine Learning – ICANN 2018 (pp. 518-527). Cham: Springer. doi:10.1007/978-3-030-01418-6_51PUB | DOI
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2018 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2920497Limberg, C., Wersing, H., & Ritter, H. (2018). Efficient Accuracy Estimation for Instance-Based Incremental Active Learning. ESANN 2018. Proceedings, 26, 171-176. Louvain-la-Neuve: i6doc.PUB