9 Publikationen
2025 | Konferenzbeitrag | FH-PUB-ID: 5904
Schöne, Marvin, et al. “Pool-Based Active Learning with Decision Trees: Incorporate the Tree Structure to Explore and Exploit.” 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx), edited by IEEE, IEEE, 2025, pp. 1–9, doi:10.1109/CITREx64975.2025.10974940.
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2025 | Konferenzbeitrag | FH-PUB-ID: 6049 | 
Schöne, Marvin, et al. “Pool-Based Active Learning with Decision Trees: Incorporate the Tree Structure to Explore and Exploit.” 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx), edited by IEEE, IEEE, 2025, pp. 1–9, doi:10.57720/6049.
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2025 | Konferenzbeitrag | FH-PUB-ID: 5905
Jaster, Bjarne, and Martin Kohlhase. “Trust Issues in Active Learning and Their Impact on Real-World Applications.” 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx Companion), edited by IEEE, IEEE, 2025, pp. 1–5, doi:10.1109/CITRExCompanion65208.2025.10981492.
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2025 | Konferenzbeitrag | FH-PUB-ID: 6045 |
Jaster, Bjarne, and Martin Kohlhase. “Trust Issues in Active Learning and Their Impact on Real-World Applications.” 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx Companion), edited by IEEE, IEEE, 2025, pp. 1–5, doi:10.57720/6045.
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2025 | Konferenzbeitrag | FH-PUB-ID: 6267
Bültemeier, Julian, et al. “AI Workflow for Scarce Data: A Modular Approach to Optimise Processes.” 2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (ETFA), IEEE, 2025, pp. 1–4, doi:10.1109/ETFA65518.2025.11205664.
HSBI-PUB
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2025 | Buchbeitrag | FH-PUB-ID: 6273 |
Schöne, Marvin, et al. “Informed Active Learning with Decision Trees to Balance Exploration and Exploitation.” Kongress KI@HSBI2025 Zukunft Im Fokus – Posterbeiträge, edited by Institute for Data Science Solutions, vol. 2, Hochschule Bielefeld, 2025, pp. 26–27, doi:10.60802/sidas.2025.2.
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2024 | Artikel | FH-PUB-ID: 6299 |
Katter, Vincent, et al. “Evaluierung der Leistungsfähigkeit von LSTM-Modellen für die Approximation physikalischer Systeme .” Schriftenreihe des Institute for Data Science Solutions, vol. 2, Hochschule Bielefeld, 2024, doi:10.60802/SIDAS.2024.2.
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2023 | Konferenzbeitrag | FH-PUB-ID: 3713 |
Jaster, Bjarne, and Martin Kohlhase. “Active Learning for Regression Problems with Ensemble Methods.” Proceedings - 33. Workshop Computational Intelligence, edited by Horst Schulte et al., Karlsruher Institut für Technologie (KIT), 2023, pp. 9–29, doi:10.5445/KSP/1000162754.
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2021 | Artikel | FH-PUB-ID: 6498 |
Guss, William Hebgen, et al. “Towards Robust and Domain Agnostic Reinforcement Learning Competitions.” ArXiv, arXiv, 2021, doi:10.48550/ARXIV.2106.03748.
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9 Publikationen
2025 | Konferenzbeitrag | FH-PUB-ID: 5904
Schöne, Marvin, et al. “Pool-Based Active Learning with Decision Trees: Incorporate the Tree Structure to Explore and Exploit.” 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx), edited by IEEE, IEEE, 2025, pp. 1–9, doi:10.1109/CITREx64975.2025.10974940.
HSBI-PUB
| DOI
| Download (ext.)
2025 | Konferenzbeitrag | FH-PUB-ID: 6049 |
Schöne, Marvin, et al. “Pool-Based Active Learning with Decision Trees: Incorporate the Tree Structure to Explore and Exploit.” 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx), edited by IEEE, IEEE, 2025, pp. 1–9, doi:10.57720/6049.
HSBI-PUB
| Dateien verfügbar
| DOI
2025 | Konferenzbeitrag | FH-PUB-ID: 5905
Jaster, Bjarne, and Martin Kohlhase. “Trust Issues in Active Learning and Their Impact on Real-World Applications.” 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx Companion), edited by IEEE, IEEE, 2025, pp. 1–5, doi:10.1109/CITRExCompanion65208.2025.10981492.
HSBI-PUB
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2025 | Konferenzbeitrag | FH-PUB-ID: 6045 |
Jaster, Bjarne, and Martin Kohlhase. “Trust Issues in Active Learning and Their Impact on Real-World Applications.” 2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx Companion), edited by IEEE, IEEE, 2025, pp. 1–5, doi:10.57720/6045.
HSBI-PUB
| Dateien verfügbar
| DOI
2025 | Konferenzbeitrag | FH-PUB-ID: 6267
Bültemeier, Julian, et al. “AI Workflow for Scarce Data: A Modular Approach to Optimise Processes.” 2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (ETFA), IEEE, 2025, pp. 1–4, doi:10.1109/ETFA65518.2025.11205664.
HSBI-PUB
| DOI
2025 | Buchbeitrag | FH-PUB-ID: 6273 |
Schöne, Marvin, et al. “Informed Active Learning with Decision Trees to Balance Exploration and Exploitation.” Kongress KI@HSBI2025 Zukunft Im Fokus – Posterbeiträge, edited by Institute for Data Science Solutions, vol. 2, Hochschule Bielefeld, 2025, pp. 26–27, doi:10.60802/sidas.2025.2.
HSBI-PUB
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2024 | Artikel | FH-PUB-ID: 6299 |
Katter, Vincent, et al. “Evaluierung der Leistungsfähigkeit von LSTM-Modellen für die Approximation physikalischer Systeme .” Schriftenreihe des Institute for Data Science Solutions, vol. 2, Hochschule Bielefeld, 2024, doi:10.60802/SIDAS.2024.2.
HSBI-PUB
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| Download (ext.)
2023 | Konferenzbeitrag | FH-PUB-ID: 3713 |
Jaster, Bjarne, and Martin Kohlhase. “Active Learning for Regression Problems with Ensemble Methods.” Proceedings - 33. Workshop Computational Intelligence, edited by Horst Schulte et al., Karlsruher Institut für Technologie (KIT), 2023, pp. 9–29, doi:10.5445/KSP/1000162754.
HSBI-PUB
| DOI
| Download (ext.)
2021 | Artikel | FH-PUB-ID: 6498 |
Guss, William Hebgen, et al. “Towards Robust and Domain Agnostic Reinforcement Learning Competitions.” ArXiv, arXiv, 2021, doi:10.48550/ARXIV.2106.03748.
HSBI-PUB
| DOI
| Download (ext.)