@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{6485,
  author       = {Migenda, Nico and Möller, Ralf and Schenck, Wolfram},
  issn         = {1932-6203},
  journal      = {PLOS One},
  number       = {1},
  publisher    = {Public Library of Science (PLoS)},
  title        = {{H-NGPCA: Hierarchical clustering of data streams with adaptive number of clusters and adaptive dimensionality}},
  doi          = {10.1371/journal.pone.0339171},
  volume       = {21},
  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{6077,
  author       = {Leuering, Julien and Jalil, Farjana and Ahmed, Qazi Arbab and Schenck, Wolfram and Jungeblut, Thorsten},
  location     = {Bielefeld},
  publisher    = {Institute for Data Science Solutions},
  title        = {{Cognitive Edge Computing for Multi-Sensor Applications with Sparse Data and High Latency Requirements}},
  year         = {2025},
}

@inproceedings{6080,
  author       = {Jalil, Farjana and Leuering, Julien and Ahmed, Qazi Arbab and Schenck, Wolfram and Jungeblut, Thorsten},
  location     = {Bielefeld},
  publisher    = { Institute for Data Science Solutions},
  title        = {{NNXC: Neural Network Meets Approximate Computing}},
  year         = {2025},
}

@inproceedings{6081,
  author       = {Jalil, Farjana and Leuering, Julien and Ahmed, Qazi Arbab and Schenck, Wolfram and Jungeblut, Thorsten},
  booktitle    = {Workshop on AI and its Applications},
  location     = {Bielefeld},
  publisher    = {Institute for Data Science Solutions},
  title        = {{AutoDSE: Towards HW/AI Co-design of Ultra-low Latency Hardware Accelerators for Industrial Applications}},
  doi          = {10.60802/sidas.2025.2},
  year         = {2025},
}

@article{6133,
  author       = {Herzig, Tim Christian and Marschner, C. and Ostrau, Christoph and Held, S. and Rickermann, J. and Schenck, Wolfram and Uphaus, Andreas and Amelung, R.},
  issn         = {1435-1269},
  journal      = {Zeitschrift für Gerontologie und Geriatrie},
  publisher    = {Springer Science and Business Media LLC},
  title        = {{Softwaregestützte Analyse geriatrischer Entlassbriefe}},
  doi          = {10.1007/s00391-025-02478-6},
  year         = {2025},
}

@inproceedings{5494,
  author       = {Akay, Julien Marteen and Schenck, Wolfram},
  booktitle    = {Artificial Neural Networks and Machine Learning – ICANN 2024. 33rd International Conference on Artificial Neural Networks, Lugano, Switzerland, September 17–20, 2024, Proceedings, Part VIII},
  editor       = {Wand, Michael and Malinovská, Kristína and Schmidhuber, Jürgen and Tetko, Igor V.},
  isbn         = {978-3-031-72352-0},
  issn         = {1611-3349},
  location     = {Lugano, Switzerland},
  pages        = {427--444},
  publisher    = {Springer Nature Switzerland},
  title        = {{Transferability of Non-contrastive Self-supervised Learning to Chronic Wound Image Recognition}},
  doi          = {10.1007/978-3-031-72353-7_31},
  year         = {2024},
}

@article{5495,
  author       = {Tharwat, Alaa and Schenck, Wolfram},
  issn         = {1558-2191},
  journal      = {IEEE Transactions on Knowledge and Data Engineering},
  number       = {8},
  pages        = {4317--4330},
  publisher    = {Institute of Electrical and Electronics Engineers (IEEE)},
  title        = {{Using Methods From Dimensionality Reduction for Active Learning With Low Query Budget}},
  doi          = {10.1109/TKDE.2024.3365189},
  volume       = {36},
  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},
}

@techreport{5498,
  author       = {Hammer, Barbara and Alaçam, Özge and Arlinghaus, Clarissa Sabrina and Brinkmann, Mona and Dörksen, Helene and Hoeken, Sanne and Jungeblut, Thorsten and Knaup, Julian and Leite, Daniel and Lohweg, Volker and Maier, Günter W. and Ngonga Ngomo, Axel-Cyrille and Othman, Alaa and Peitz, Sebastian and Platzner, Marco and Pütz, Ole and Röcker, Carsten and Röder, Michael and Schenck, Wolfram and Schneider, Axel and Schwandt, Silke and Spliethoff, Sophie and Straat, Michiel and Sürmeli, Baris Gün and Vollmer, Anna-Lisa and Zarrieß, Sina},
  publisher    = {Bielefeld University},
  title        = {{Sustainable Life-Cycle of Intelligent Socio-Technical Systems}},
  doi          = {10.4119/UNIBI/2992602},
  year         = {2024},
}

@article{5499,
  author       = {Shah, Zafran Hussain and Müller, Marcel and Hübner, Wolfgang and Ortkrass, Henning and Hammer, Barbara and Huser, Thomas and Schenck, Wolfram},
  issn         = {2624-8212},
  journal      = {Frontiers in Artificial Intelligence},
  publisher    = {Frontiers Media SA},
  title        = {{Image restoration in frequency space using complex-valued CNNs}},
  doi          = {10.3389/frai.2024.1353873},
  volume       = {7},
  year         = {2024},
}

@article{5500,
  author       = {Shah, Zafran Hussain and Müller, Marcel and Hübner, Wolfgang and Wang, Tung-Cheng and Telman, Daniel and Huser, Thomas and Schenck, Wolfram},
  issn         = {2047-217X},
  journal      = {GigaScience},
  publisher    = {Oxford University Press (OUP)},
  title        = {{Evaluation of Swin Transformer and knowledge transfer for denoising of super-resolution structured illumination microscopy data}},
  doi          = {10.1093/gigascience/giad109},
  volume       = {13},
  year         = {2024},
}

@article{5566,
  author       = {Tharwat, Alaa and Schenck, Wolfram},
  issn         = {1558-2191},
  journal      = {IEEE Transactions on Knowledge and Data Engineering},
  number       = {8},
  pages        = {4317--4330},
  publisher    = {Institute of Electrical and Electronics Engineers (IEEE)},
  title        = {{Using Methods From Dimensionality Reduction for Active Learning With Low Query Budget}},
  doi          = {10.1109/TKDE.2024.3365189},
  volume       = {36},
  year         = {2024},
}

@article{5568,
  author       = {Tharwat, Alaa and Schenck, Wolfram},
  issn         = {2162-2388},
  journal      = {IEEE Transactions on Neural Networks and Learning Systems},
  number       = {2},
  pages        = {3273--3287},
  publisher    = {Institute of Electrical and Electronics Engineers (IEEE)},
  title        = {{Active Learning for Handling Missing Data}},
  doi          = {10.1109/TNNLS.2024.3352279},
  volume       = {36},
  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{4644,
  author       = {Klein, Lukas and Ostrau, Christoph and Thies, Michael and Schenck, Wolfram and Rückert, Ulrich},
  booktitle    = {Pervasive Computing Technologies for Healthcare. 17th EAI International Conference, PervasiveHealth 2023, Malmö, Sweden, November 27-29, 2023, Proceedings},
  editor       = {Salvi, Dario and Van Gorp, Pieter and Shah, Syed Ahmar},
  isbn         = {978-3-031-59716-9},
  issn         = {1867-822X},
  location     = {Malmö, Schweden},
  pages        = {423--437},
  publisher    = {Springer Nature Switzerland},
  title        = {{Exploratory Analysis of Machine Learning Methods for the Prognosis of Falls in Elderly Care Based on Accelerometer Data}},
  doi          = {10.1007/978-3-031-59717-6_27},
  year         = {2024},
}

@article{4698,
  author       = {Migenda, Nico and Möller, Ralf and Schenck, Wolfram},
  issn         = {2665-9638},
  journal      = {Software Impacts},
  publisher    = {Elsevier BV},
  title        = {{NGPCA: Clustering of high-dimensional and non-stationary data streams}},
  doi          = {10.1016/j.simpa.2024.100635},
  volume       = {20},
  year         = {2024},
}