9 Publikationen
2025 | Konferenzbeitrag | FH-PUB-ID: 5904
Schöne, M., Jaster, B., Bültemeier, J., Kösters, J., Holst, C.-A., & Kohlhase, M. (2025). Pool-based Active Learning with Decision Trees: Incorporate the Tree Structure to Explore and Exploit. In IEEE (Ed.), 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx) (pp. 1–9). Trondheim, Norway: IEEE. https://doi.org/10.1109/CITREx64975.2025.10974940
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2025 | Konferenzbeitrag | FH-PUB-ID: 6049 | 
Schöne, M., Jaster, B., Bültemeier, J., Kösters, J., Holst, C.-A., & Kohlhase, M. (2025). Pool-based Active Learning with Decision Trees: Incorporate the Tree Structure to Explore and Exploit. In IEEE (Ed.), 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx) (pp. 1–9). Trondheim, Norway: IEEE. https://doi.org/10.57720/6049
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2025 | Konferenzbeitrag | FH-PUB-ID: 5905
Jaster, B., & Kohlhase, M. (2025). Trust Issues in Active Learning and Their Impact on Real-World Applications. In IEEE (Ed.), 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx Companion) (pp. 1–5). Trondheim, Norway: IEEE. https://doi.org/10.1109/CITRExCompanion65208.2025.10981492
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2025 | Konferenzbeitrag | FH-PUB-ID: 6045 |
Jaster, B., & Kohlhase, M. (2025). Trust Issues in Active Learning and Their Impact on Real-World Applications. In IEEE (Ed.), 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx Companion) (pp. 1–5). Trondheim, Norway: IEEE. https://doi.org/10.57720/6045
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2025 | Konferenzbeitrag | FH-PUB-ID: 6267
Bültemeier, J., Holst, C.-A., Lohweg, V., Schöne, M., Jaster, B., & Kohlhase, M. (2025). AI Workflow for Scarce Data: A Modular Approach to Optimise Processes. In 2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (ETFA) (pp. 1–4). Porto, Portugal: IEEE. https://doi.org/10.1109/ETFA65518.2025.11205664
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2025 | Buchbeitrag | FH-PUB-ID: 6273 |
Schöne, M., Jaster, B., Bültemeier, J., & Kohlhase, M. (2025). Informed Active Learning with Decision Trees to Balance Exploration and Exploitation. In Institute for Data Science Solutions (Ed.), Kongress KI@HSBI2025 Zukunft im Fokus – Posterbeiträge (Vol. 2, pp. 26–27). Bielefeld: Hochschule Bielefeld. https://doi.org/10.60802/sidas.2025.2
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2024 | Artikel | FH-PUB-ID: 6299 |
Katter, V., Jaster, B., & Schöne, M. (2024). Evaluierung der Leistungsfähigkeit von LSTM-Modellen für die Approximation physikalischer Systeme . Schriftenreihe des Institute for Data Science Solutions, 2. https://doi.org/10.60802/SIDAS.2024.2
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2023 | Konferenzbeitrag | FH-PUB-ID: 3713 |
Jaster, B., & Kohlhase, M. (2023). Active Learning for Regression Problems with Ensemble Methods. In H. Schulte, F. Hoffmann, & R. Mikut (Eds.), Proceedings - 33. Workshop Computational Intelligence (pp. 9–29). Berlin: Karlsruher Institut für Technologie (KIT). https://doi.org/10.5445/KSP/1000162754
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2021 | Artikel | FH-PUB-ID: 6498 |
Guss, W. H., Milani, S., Topin, N., Houghton, B., Mohanty, S., Melnik, A., … Juceviciute, G. (2021). Towards robust and domain agnostic reinforcement learning competitions. ArXiv. https://doi.org/10.48550/ARXIV.2106.03748
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9 Publikationen
2025 | Konferenzbeitrag | FH-PUB-ID: 5904
Schöne, M., Jaster, B., Bültemeier, J., Kösters, J., Holst, C.-A., & Kohlhase, M. (2025). Pool-based Active Learning with Decision Trees: Incorporate the Tree Structure to Explore and Exploit. In IEEE (Ed.), 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx) (pp. 1–9). Trondheim, Norway: IEEE. https://doi.org/10.1109/CITREx64975.2025.10974940
HSBI-PUB
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2025 | Konferenzbeitrag | FH-PUB-ID: 6049 |
Schöne, M., Jaster, B., Bültemeier, J., Kösters, J., Holst, C.-A., & Kohlhase, M. (2025). Pool-based Active Learning with Decision Trees: Incorporate the Tree Structure to Explore and Exploit. In IEEE (Ed.), 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx) (pp. 1–9). Trondheim, Norway: IEEE. https://doi.org/10.57720/6049
HSBI-PUB
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2025 | Konferenzbeitrag | FH-PUB-ID: 5905
Jaster, B., & Kohlhase, M. (2025). Trust Issues in Active Learning and Their Impact on Real-World Applications. In IEEE (Ed.), 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx Companion) (pp. 1–5). Trondheim, Norway: IEEE. https://doi.org/10.1109/CITRExCompanion65208.2025.10981492
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2025 | Konferenzbeitrag | FH-PUB-ID: 6045 |
Jaster, B., & Kohlhase, M. (2025). Trust Issues in Active Learning and Their Impact on Real-World Applications. In IEEE (Ed.), 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx Companion) (pp. 1–5). Trondheim, Norway: IEEE. https://doi.org/10.57720/6045
HSBI-PUB
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| DOI
2025 | Konferenzbeitrag | FH-PUB-ID: 6267
Bültemeier, J., Holst, C.-A., Lohweg, V., Schöne, M., Jaster, B., & Kohlhase, M. (2025). AI Workflow for Scarce Data: A Modular Approach to Optimise Processes. In 2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (ETFA) (pp. 1–4). Porto, Portugal: IEEE. https://doi.org/10.1109/ETFA65518.2025.11205664
HSBI-PUB
| DOI
2025 | Buchbeitrag | FH-PUB-ID: 6273 |
Schöne, M., Jaster, B., Bültemeier, J., & Kohlhase, M. (2025). Informed Active Learning with Decision Trees to Balance Exploration and Exploitation. In Institute for Data Science Solutions (Ed.), Kongress KI@HSBI2025 Zukunft im Fokus – Posterbeiträge (Vol. 2, pp. 26–27). Bielefeld: Hochschule Bielefeld. https://doi.org/10.60802/sidas.2025.2
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2024 | Artikel | FH-PUB-ID: 6299 |
Katter, V., Jaster, B., & Schöne, M. (2024). Evaluierung der Leistungsfähigkeit von LSTM-Modellen für die Approximation physikalischer Systeme . Schriftenreihe des Institute for Data Science Solutions, 2. https://doi.org/10.60802/SIDAS.2024.2
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2023 | Konferenzbeitrag | FH-PUB-ID: 3713 |
Jaster, B., & Kohlhase, M. (2023). Active Learning for Regression Problems with Ensemble Methods. In H. Schulte, F. Hoffmann, & R. Mikut (Eds.), Proceedings - 33. Workshop Computational Intelligence (pp. 9–29). Berlin: Karlsruher Institut für Technologie (KIT). https://doi.org/10.5445/KSP/1000162754
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2021 | Artikel | FH-PUB-ID: 6498 |
Guss, W. H., Milani, S., Topin, N., Houghton, B., Mohanty, S., Melnik, A., … Juceviciute, G. (2021). Towards robust and domain agnostic reinforcement learning competitions. ArXiv. https://doi.org/10.48550/ARXIV.2106.03748
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| Download (ext.)