9 Publikationen
2025 | Konferenzbeitrag | FH-PUB-ID: 5904
Schöne M, Jaster B, Bültemeier J, Kösters J, Holst C-A, Kohlhase M. 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). IEEE; 2025:1-9. doi: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. 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). IEEE; 2025:1-9. doi:10.57720/6049
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2025 | Konferenzbeitrag | FH-PUB-ID: 5905
Jaster B, Kohlhase M. 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). IEEE; 2025:1-5. doi:10.1109/CITRExCompanion65208.2025.10981492
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2025 | Konferenzbeitrag | FH-PUB-ID: 6045 |
Jaster B, Kohlhase M. 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). IEEE; 2025:1-5. doi: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. AI Workflow for Scarce Data: A Modular Approach to Optimise Processes. In: 2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (ETFA). IEEE; 2025:1-4. doi:10.1109/ETFA65518.2025.11205664
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2025 | Buchbeitrag | FH-PUB-ID: 6273 |
Schöne M, Jaster B, Bültemeier J, Kohlhase M. 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. Schriftenreihe des Institute for Data Science Solutions. Bielefeld: Hochschule Bielefeld; 2025:26-27. doi:10.60802/sidas.2025.2
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2024 | Artikel | FH-PUB-ID: 6299 |
Katter V, Jaster B, Schöne M. Evaluierung der Leistungsfähigkeit von LSTM-Modellen für die Approximation physikalischer Systeme . Schriftenreihe des Institute for Data Science Solutions. 2024;2. doi:10.60802/SIDAS.2024.2
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2023 | Konferenzbeitrag | FH-PUB-ID: 3713 |
Jaster B, Kohlhase M. Active Learning for Regression Problems with Ensemble Methods. In: Schulte H, Hoffmann F, Mikut R, eds. Proceedings - 33. Workshop Computational Intelligence. Karlsruher Institut für Technologie (KIT); 2023:9-29. doi:10.5445/KSP/1000162754
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2021 | Artikel | FH-PUB-ID: 6498 |
Guss WH, Milani S, Topin N, et al. Towards robust and domain agnostic reinforcement learning competitions. arXiv. 2021. doi: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. 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). IEEE; 2025:1-9. doi: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. 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). IEEE; 2025:1-9. doi:10.57720/6049
HSBI-PUB
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2025 | Konferenzbeitrag | FH-PUB-ID: 5905
Jaster B, Kohlhase M. 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). IEEE; 2025:1-5. doi:10.1109/CITRExCompanion65208.2025.10981492
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2025 | Konferenzbeitrag | FH-PUB-ID: 6045 |
Jaster B, Kohlhase M. 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). IEEE; 2025:1-5. doi: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. AI Workflow for Scarce Data: A Modular Approach to Optimise Processes. In: 2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (ETFA). IEEE; 2025:1-4. doi:10.1109/ETFA65518.2025.11205664
HSBI-PUB
| DOI
2025 | Buchbeitrag | FH-PUB-ID: 6273 |
Schöne M, Jaster B, Bültemeier J, Kohlhase M. 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. Schriftenreihe des Institute for Data Science Solutions. Bielefeld: Hochschule Bielefeld; 2025:26-27. doi:10.60802/sidas.2025.2
HSBI-PUB
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2024 | Artikel | FH-PUB-ID: 6299 |
Katter V, Jaster B, Schöne M. Evaluierung der Leistungsfähigkeit von LSTM-Modellen für die Approximation physikalischer Systeme . Schriftenreihe des Institute for Data Science Solutions. 2024;2. doi:10.60802/SIDAS.2024.2
HSBI-PUB
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| Download (ext.)
2023 | Konferenzbeitrag | FH-PUB-ID: 3713 |
Jaster B, Kohlhase M. Active Learning for Regression Problems with Ensemble Methods. In: Schulte H, Hoffmann F, Mikut R, eds. Proceedings - 33. Workshop Computational Intelligence. Karlsruher Institut für Technologie (KIT); 2023:9-29. doi:10.5445/KSP/1000162754
HSBI-PUB
| DOI
| Download (ext.)
2021 | Artikel | FH-PUB-ID: 6498 |
Guss WH, Milani S, Topin N, et al. Towards robust and domain agnostic reinforcement learning competitions. arXiv. 2021. doi:10.48550/ARXIV.2106.03748
HSBI-PUB
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| Download (ext.)