@inproceedings{6898, abstract = {The labeling process for supervised learning is costly and time-consuming, and is often impractical to scale due to real-world constraints. Active learning (AL) addresses this challenge by strategically selecting representative and informative data points to reduce labeling efforts. This paper focuses on an AL scenario in which only a very limited number of labels can be acquired. We propose an algorithm operating in two phases: (1) an exploration phase that prioritizes representative and diverse data points using density-driven criteria, and (2) an exploitation phase that combines predictive uncertainty with density weighting to select informative samples from densely populated regions. This enhances both representativeness and informativeness. Our results demonstrate significant improvements in model quality compared to other algorithms typically employed for this scenario, across various scenarios involving imbalanced data in classification tasks and skewness in regression tasks. Through this work, we aim to provide a new algorithm for this scenario and investigate general principles for AL. While most AL studies focus on either classification or regression, our work applies the algorithms to both. Therefore, we can analyze the differences between classification and regression problems and their effects on AL strategies. Furthermore, we explore different categories of AL criteria and their effectiveness in the low-budget regime. These results also provide insight into the cold-start problem, which involves selecting an initial labeled set and is faced by many model-based AL methods.}, author = {Jaster, Bjarne and Tharwat, Alaa and Sheikh, Eiram Mahera and Kohlhase, Martin and Schenck, Wolfram}, booktitle = {Machine Learning and Principles and Practice of Knowledge Discovery in Databases. International Workshops of ECML PKDD 2025, Porto, Portugal, September 15–19, 2025, Revised Selected Papers, Part IV}, editor = {Koprinska, Irena and Mendes-Moreira, João and Branco, Paula}, isbn = {978-3-032-19104-5}, issn = {1865-0937}, location = {Porto, Portugal}, pages = {5--21}, publisher = {Springer Nature Switzerland}, title = {{Low Query Budget Active Learning for Classification and Regression}}, doi = {10.1007/978-3-032-19105-2_1}, year = {2026}, } @article{6655, author = {Tharwat, Alaa and Jaster, Bjarne and Schenck, Wolfram and Kohlhase, Martin}, issn = {09521976}, journal = {Engineering Applications of Artificial Intelligence}, publisher = {Elsevier BV}, title = {{Active learning evaluation metrics for classification and regression frameworks}}, doi = {10.1016/j.engappai.2026.114295}, volume = {171}, year = {2026}, } @article{6244, author = {Niederhaus, Marvin and Migenda, Nico and Weller, Julian and Kohlhase, Martin and Schenck, Wolfram}, issn = {2504-2289}, journal = {Big Data and Cognitive Computing}, keywords = {prescriptive analytics, prescriptive platforms, advanced data analytics, retrieval-augmented generation, graph-based retrieval-augmented generation, large language models, generative AI, genAI, recommender system}, number = {10}, publisher = {MDPI AG}, title = {{Integrating Graph Retrieval-Augmented Generation into Prescriptive Recommender Systems}}, doi = {10.3390/bdcc9100261}, volume = {9}, year = {2025}, } @inproceedings{6298, author = {Katter, Vincent and Kohlhase, Martin}, booktitle = {Proceedings – 35. Workshop Computational Intelligence: Berlin, 20.–21. November 2025}, editor = {Schulte, Horst and Hoffmann, Frank and Mikut, Ralf}, location = {Berlin}, pages = {89--96}, publisher = {Karlsruher Institut für Technologie (KIT)}, title = {{Efficient Gait Analysis using Knowledge Distillation from Sparse Sensors}}, doi = {10.5445/IR/1000186052}, year = {2025}, } @article{6268, author = {Schöne, Marvin and Kohlhase, Martin and Nelles, Oliver}, issn = {2196-677X}, journal = {at - Automatisierungstechnik}, number = {10}, pages = {727--739}, publisher = {Walter de Gruyter GmbH}, title = {{Incorporation of structural properties of the response surface into oblique model trees}}, doi = {10.1515/auto-2025-0017}, volume = {73}, year = {2025}, } @inproceedings{6825, author = {Vogel, Leon and Vollenkemper, Lukas and Müller, Arthur and Kohlhase, Martin}, booktitle = {Preface: 2025 The 12th International Conference on Industrial Engineering and Applications (Europe)}, editor = {Sheu, Shey-Huei}, location = {München }, publisher = {AIP Publishing}, title = {{Scheduling individualized products with reinforcement learning to reduce worker stress}}, doi = {10.1063/5.0315901}, volume = {3381}, year = {2025}, } @inproceedings{6371, author = {Dockhorn, Frederick-Mortimer and Kohlhase, Martin}, booktitle = {Proceedings - 35. Workshop Computational Intelligence}, editor = {Schulte, Horst and Hoffmann, Frank and Mikut, Ralf}, publisher = {Karlsruher Institut für Technologie (KIT)}, title = {{Discrepancy Modeling for Dynamical Systems}}, doi = {10.5445/IR/1000186052}, year = {2025}, } @inproceedings{6267, author = {Bültemeier, Julian and Holst, Christoph-Alexander and Lohweg, Volker and Schöne, Marvin and Jaster, Bjarne and Kohlhase, Martin}, booktitle = {2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (ETFA)}, location = {Porto, Portugal}, pages = {1--4}, publisher = {IEEE}, title = {{AI Workflow for Scarce Data: A Modular Approach to Optimise Processes}}, doi = {10.1109/ETFA65518.2025.11205664}, year = {2025}, } @inbook{6273, author = {Schöne, Marvin and Jaster, Bjarne and Bültemeier, Julian and Kohlhase, Martin}, booktitle = {Kongress KI@HSBI2025 Zukunft im Fokus – Posterbeiträge}, pages = {26--27}, publisher = {Hochschule Bielefeld}, title = {{Informed Active Learning with Decision Trees to Balance Exploration and Exploitation}}, doi = {10.60802/sidas.2025.2}, volume = {2}, year = {2025}, } @article{6297, author = {Katter, Vincent and Huperz, Carolin and Kohlhase, Martin and Bartsch, J. and Özlu, I and Regier, M and Amelung, R.I. and Klemme, B.}, issn = {0340-5591}, journal = {Orthopädie Technik}, keywords = {Diabetisches Fußsyndrom (DFS), Smarte Orthese, Plantardruckmessung, Anomalieerkennung, Künstliche Intelligenz}, number = {11}, pages = {68 -- 73}, publisher = {Verlag Orthopädie-Technik}, title = {{Sensorintegration in Orthesen zur Versorgung des Diabetischen Fußsyndroms: eine technische Betrachtung}}, year = {2025}, } @inproceedings{5905, author = {Jaster, Bjarne and Kohlhase, Martin}, booktitle = {2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx Companion)}, keywords = {Active Learning, Trustworthiness, Evaluation-methods}, location = {Trondheim, Norway}, pages = {1--5}, publisher = {IEEE}, title = {{Trust Issues in Active Learning and Their Impact on Real-World Applications}}, doi = {10.1109/CITRExCompanion65208.2025.10981492}, year = {2025}, } @inproceedings{6045, author = {Jaster, Bjarne and Kohlhase, Martin}, booktitle = {2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx Companion)}, keywords = {Active Learning, Trustworthiness, Evaluation-methods}, location = {Trondheim, Norway}, pages = {1--5}, publisher = {IEEE}, title = {{Trust Issues in Active Learning and Their Impact on Real-World Applications}}, doi = {10.57720/6045}, year = {2025}, } @inproceedings{6049, author = {Schöne, Marvin and Jaster, Bjarne and Bültemeier, Julian and Kösters, Justus and Holst, Christoph-Alexander and Kohlhase, Martin}, booktitle = {2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx)}, keywords = {Interpretability, Classification, Pool-based Active Learning, Decision Trees}, location = {Trondheim, Norway}, pages = {1--9}, publisher = {IEEE}, title = {{Pool-based Active Learning with Decision Trees: Incorporate the Tree Structure to Explore and Exploit}}, doi = {10.57720/6049}, year = {2025}, } @inproceedings{5904, author = {Schöne, Marvin and Jaster, Bjarne and Bültemeier, Julian and Kösters, Justus and Holst, Christoph-Alexander and Kohlhase, Martin}, booktitle = {2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx)}, keywords = {Interpretability, Classification, Pool-based Active Learning, Decision Trees}, location = {Trondheim, Norway}, pages = {1--9}, publisher = {IEEE}, title = {{Pool-based Active Learning with Decision Trees: Incorporate the Tree Structure to Explore and Exploit}}, doi = {10.1109/CITREx64975.2025.10974940}, year = {2025}, } @inproceedings{5882, author = {Bültemeier, Julian and Schöne, Marvin and Kohlhase, Martin and Holst, Christoph-Alexander and Lohweg, Volker and Nelles, Oliver}, booktitle = {Proceedings - 34. Workshop Computational Intelligence: Berlin, 21.-22. November 2024}, editor = {Schulte, Horst and Hoffmann, Frank and Mikut, Ralf }, isbn = {9783731513889}, location = {Berlin}, pages = {217--231}, publisher = {KIT Scientific Publishing}, title = {{Dichte-skaliertes Optimierungskriterium für Sliced Latin Hypercube Designs}}, doi = {10.58895/ksp//1000174544-14}, year = {2024}, } @inproceedings{5789, author = {Dockhorn, Frederick-Mortimer and Kohlhase, Martin}, booktitle = {Proceedings - 34. Workshop Computational Intelligence: Berlin, 21.-22. November 2024}, editor = {Schulte, Horst and Hoffmann, Frank and Mikut, Ralf }, isbn = { 978-3-7315-1388-9}, location = {Berlin}, pages = {53--76}, publisher = {KIT Scientific Publishing}, title = {{An Application-oriented Review of Standard and Integral Sparse Identification of Nonlinear Dynamics}}, doi = {10.5445/KSP/1000174544}, year = {2024}, } @article{5497, author = {Weller, Julian and Migenda, Nico and Enzberg, Sebastian von and Kohlhase, Martin and Schenck, Wolfram and Dumitrescu, Roman}, issn = {2212-8271}, journal = {Procedia CIRP}, pages = {424--429}, publisher = {Elsevier BV}, title = {{Design decisions for integrating Prescriptive Analytics Use Cases into Smart Factories}}, doi = {10.1016/j.procir.2024.03.022}, volume = {128}, year = {2024}, } @article{4913, author = {Weller, Julian and Migenda, Nico and Naik, Yash and Heuwinkel, Tim and Kühn, Arno and Kohlhase, Martin and Schenck, Wolfram and Dumitrescu, Roman}, issn = {2227-7390}, journal = {Mathematics}, number = {17}, publisher = {MDPI AG}, title = {{Reference Architecture for the Integration of Prescriptive Analytics Use Cases in Smart Factories}}, doi = {10.3390/math12172663}, volume = {12}, year = {2024}, } @inbook{4915, author = {Weller, Julian and Migenda, Nico and Liu, Rui and Wegel, Arthur and von Enzberg, Sebastian and Kohlhase, Martin and Schenck, Wolfram and Dumitrescu, Roman}, booktitle = {Machine Learning for Cyber-Physical Systems. Selected papers from the International Conference ML4CPS 2023}, editor = {Niggemann, Oliver and Beyerer, Jürgen and Krantz, Maria and Kühnert, Christian}, isbn = {978-3-031-47061-5}, issn = {2522-8587}, pages = {89--100}, publisher = {Springer Nature Switzerland}, title = {{Towards a Systematic Approach for Prescriptive Analytics Use Cases in Smart Factories}}, doi = {10.1007/978-3-031-47062-2_9}, volume = {18}, year = {2024}, } @inproceedings{4699, author = {Niederhaus, Marvin and Migenda, Nico and Weller, Julian and Schenck, Wolfram and Kohlhase, Martin}, booktitle = {2024 35th Conference of Open Innovations Association (FRUCT)}, location = {Tampere, Finland}, pages = {509--519}, publisher = {IEEE}, title = {{Technical Readiness of Prescriptive Analytics Platforms: A Survey}}, doi = {10.23919/FRUCT61870.2024.10516367}, year = {2024}, }