[{"title":"Low Query Budget Active Learning for Classification and Regression","date_created":"2026-05-10T07:55:29Z","user_id":"226669","main_file_link":[{"open_access":"1","url":"https://rdcu.be/fh03T"}],"alternative_id":["6899"],"publication_identifier":{"issn":["1865-0929"],"eisbn":["978-3-032-19105-2"],"isbn":["978-3-032-19104-5"],"eissn":["1865-0937"]},"type":"conference","project":[{"_id":"f432a2ee-bceb-11ed-a251-a83585c5074d","name":"Institute for Data Science Solutions"},{"name":"Institut für Systemdynamik und Mechatronik","_id":"beb248c8-cd75-11ed-b77c-e432b4711f7b"}],"oa":"1","publication_status":"published","series_title":"Communications in Computer and Information Science","publication":"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","conference":{"location":"Porto, Portugal","name":"ECML PKDD 2025","end_date":"2025-09-19","start_date":"2025-09-15"},"status":"public","place":"Cham","citation":{"chicago":"Jaster, Bjarne, Alaa Tharwat, Eiram Mahera Sheikh, Martin Kohlhase, and Wolfram Schenck. “Low Query Budget Active Learning for Classification and Regression.” In <i>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</i>, edited by Irena Koprinska, João Mendes-Moreira, and Paula Branco, 5–21. Communications in Computer and Information Science. Cham: Springer Nature Switzerland, 2026. <a href=\"https://doi.org/10.1007/978-3-032-19105-2_1\">https://doi.org/10.1007/978-3-032-19105-2_1</a>.","short":"B. Jaster, A. Tharwat, E.M. Sheikh, M. Kohlhase, W. Schenck, in: I. Koprinska, J. Mendes-Moreira, P. Branco (Eds.), 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, Springer Nature Switzerland, Cham, 2026, pp. 5–21.","ama":"Jaster B, Tharwat A, Sheikh EM, Kohlhase M, Schenck W. Low Query Budget Active Learning for Classification and Regression. In: Koprinska I, Mendes-Moreira J, Branco P, eds. <i>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</i>. Communications in Computer and Information Science. Cham: Springer Nature Switzerland; 2026:5-21. doi:<a href=\"https://doi.org/10.1007/978-3-032-19105-2_1\">10.1007/978-3-032-19105-2_1</a>","mla":"Jaster, Bjarne, et al. “Low Query Budget Active Learning for Classification and Regression.” <i>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</i>, edited by Irena Koprinska et al., Springer Nature Switzerland, 2026, pp. 5–21, doi:<a href=\"https://doi.org/10.1007/978-3-032-19105-2_1\">10.1007/978-3-032-19105-2_1</a>.","ieee":"B. Jaster, A. Tharwat, E. M. Sheikh, M. Kohlhase, and W. Schenck, “Low Query Budget Active Learning for Classification and Regression,” in <i>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</i>, Porto, Portugal, 2026, pp. 5–21.","bibtex":"@inproceedings{Jaster_Tharwat_Sheikh_Kohlhase_Schenck_2026, place={Cham}, series={Communications in Computer and Information Science}, title={Low Query Budget Active Learning for Classification and Regression}, DOI={<a href=\"https://doi.org/10.1007/978-3-032-19105-2_1\">10.1007/978-3-032-19105-2_1</a>}, 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}, publisher={Springer Nature Switzerland}, author={Jaster, Bjarne and Tharwat, Alaa and Sheikh, Eiram Mahera and Kohlhase, Martin and Schenck, Wolfram}, editor={Koprinska, Irena and Mendes-Moreira, João and Branco, PaulaEditors}, year={2026}, pages={5–21}, collection={Communications in Computer and Information Science} }","apa":"Jaster, B., Tharwat, A., Sheikh, E. M., Kohlhase, M., &#38; Schenck, W. (2026). Low Query Budget Active Learning for Classification and Regression. In I. Koprinska, J. Mendes-Moreira, &#38; P. Branco (Eds.), <i>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</i> (pp. 5–21). Cham: Springer Nature Switzerland. <a href=\"https://doi.org/10.1007/978-3-032-19105-2_1\">https://doi.org/10.1007/978-3-032-19105-2_1</a>","alphadin":"<span style=\"font-variant:small-caps;\">Jaster, Bjarne</span> ; <span style=\"font-variant:small-caps;\">Tharwat, Alaa</span> ; <span style=\"font-variant:small-caps;\">Sheikh, Eiram Mahera</span> ; <span style=\"font-variant:small-caps;\">Kohlhase, Martin</span> ; <span style=\"font-variant:small-caps;\">Schenck, Wolfram</span>: Low Query Budget Active Learning for Classification and Regression. In: <span style=\"font-variant:small-caps;\">Koprinska, I.</span> ; <span style=\"font-variant:small-caps;\">Mendes-Moreira, J.</span> ; <span style=\"font-variant:small-caps;\">Branco, P.</span> (Hrsg.): <i>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</i>, <i>Communications in Computer and Information Science</i>. Cham : Springer Nature Switzerland, 2026, S. 5–21"},"author":[{"id":"252434","first_name":"Bjarne","full_name":"Jaster, Bjarne","orcid":"0000-0002-8362-5369","last_name":"Jaster"},{"last_name":"Tharwat","full_name":"Tharwat, Alaa","first_name":"Alaa","id":"238549"},{"last_name":"Sheikh","full_name":"Sheikh, Eiram Mahera","first_name":"Eiram Mahera"},{"last_name":"Kohlhase","full_name":"Kohlhase, Martin","orcid":"0009-0002-9374-0720","id":"226669","first_name":"Martin"},{"id":"224375","first_name":"Wolfram","full_name":"Schenck, Wolfram","orcid":"0000-0003-3300-2048","last_name":"Schenck"}],"publisher":"Springer Nature Switzerland","page":"5-21","date_updated":"2026-06-01T15:18:27Z","doi":"10.1007/978-3-032-19105-2_1","language":[{"iso":"eng"}],"year":"2026","_id":"6898","editor":[{"full_name":"Koprinska, Irena","last_name":"Koprinska","first_name":"Irena"},{"first_name":"João","full_name":"Mendes-Moreira, João","last_name":"Mendes-Moreira"},{"first_name":"Paula","full_name":"Branco, Paula","last_name":"Branco"}],"abstract":[{"text":"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.","lang":"eng"}]},{"_id":"6655","year":"2026","language":[{"iso":"eng"}],"article_number":"114295","author":[{"full_name":"Tharwat, Alaa","last_name":"Tharwat","first_name":"Alaa","id":"238549"},{"first_name":"Bjarne","id":"252434","orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0002-8362-5369/work/207108820","orcid":"0000-0002-8362-5369","full_name":"Jaster, Bjarne","last_name":"Jaster"},{"full_name":"Schenck, Wolfram","orcid":"0000-0003-3300-2048","last_name":"Schenck","orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0003-3300-2048/work/207108821","id":"224375","first_name":"Wolfram"},{"full_name":"Kohlhase, Martin","orcid":"0009-0002-9374-0720","last_name":"Kohlhase","orcid_put_code_url":"https://api.orcid.org/v2.0/0009-0002-9374-0720/work/207108822","id":"226669","first_name":"Martin"}],"citation":{"apa":"Tharwat, A., Jaster, B., Schenck, W., &#38; Kohlhase, M. (2026). Active learning evaluation metrics for classification and regression frameworks. <i>Engineering Applications of Artificial Intelligence</i>, <i>171</i>. <a href=\"https://doi.org/10.1016/j.engappai.2026.114295\">https://doi.org/10.1016/j.engappai.2026.114295</a>","bibtex":"@article{Tharwat_Jaster_Schenck_Kohlhase_2026, title={Active learning evaluation metrics for classification and regression frameworks}, volume={171}, DOI={<a href=\"https://doi.org/10.1016/j.engappai.2026.114295\">10.1016/j.engappai.2026.114295</a>}, number={114295}, journal={Engineering Applications of Artificial Intelligence}, publisher={Elsevier BV}, author={Tharwat, Alaa and Jaster, Bjarne and Schenck, Wolfram and Kohlhase, Martin}, year={2026} }","alphadin":"<span style=\"font-variant:small-caps;\">Tharwat, Alaa</span> ; <span style=\"font-variant:small-caps;\">Jaster, Bjarne</span> ; <span style=\"font-variant:small-caps;\">Schenck, Wolfram</span> ; <span style=\"font-variant:small-caps;\">Kohlhase, Martin</span>: Active learning evaluation metrics for classification and regression frameworks. In: <i>Engineering Applications of Artificial Intelligence</i> Bd. 171, Elsevier BV (2026)","ieee":"A. Tharwat, B. Jaster, W. Schenck, and M. Kohlhase, “Active learning evaluation metrics for classification and regression frameworks,” <i>Engineering Applications of Artificial Intelligence</i>, vol. 171, 2026.","ama":"Tharwat A, Jaster B, Schenck W, Kohlhase M. Active learning evaluation metrics for classification and regression frameworks. <i>Engineering Applications of Artificial Intelligence</i>. 2026;171. doi:<a href=\"https://doi.org/10.1016/j.engappai.2026.114295\">10.1016/j.engappai.2026.114295</a>","mla":"Tharwat, Alaa, et al. “Active Learning Evaluation Metrics for Classification and Regression Frameworks.” <i>Engineering Applications of Artificial Intelligence</i>, vol. 171, 114295, Elsevier BV, 2026, doi:<a href=\"https://doi.org/10.1016/j.engappai.2026.114295\">10.1016/j.engappai.2026.114295</a>.","short":"A. Tharwat, B. Jaster, W. Schenck, M. Kohlhase, Engineering Applications of Artificial Intelligence 171 (2026).","chicago":"Tharwat, Alaa, Bjarne Jaster, Wolfram Schenck, and Martin Kohlhase. “Active Learning Evaluation Metrics for Classification and Regression Frameworks.” <i>Engineering Applications of Artificial Intelligence</i> 171 (2026). <a href=\"https://doi.org/10.1016/j.engappai.2026.114295\">https://doi.org/10.1016/j.engappai.2026.114295</a>."},"status":"public","doi":"10.1016/j.engappai.2026.114295","intvolume":"       171","date_updated":"2026-06-01T15:11:58Z","publisher":"Elsevier BV","project":[{"_id":"f432a2ee-bceb-11ed-a251-a83585c5074d","name":"Institute for Data Science Solutions"},{"_id":"beb248c8-cd75-11ed-b77c-e432b4711f7b","name":"Institut für Systemdynamik und Mechatronik"}],"oa":"1","type":"journal_article","publication_identifier":{"issn":["09521976"]},"main_file_link":[{"open_access":"1","url":"https://doi.org/10.1016/j.engappai.2026.114295"}],"user_id":"226669","publication":"Engineering Applications of Artificial Intelligence","publication_status":"published","date_created":"2026-02-27T10:10:55Z","title":"Active learning evaluation metrics for classification and regression frameworks","volume":171},{"year":"2025","_id":"6267","language":[{"iso":"eng"}],"doi":"10.1109/ETFA65518.2025.11205664","publisher":"IEEE","page":"1-4","date_updated":"2026-03-17T15:29:28Z","citation":{"short":"J. Bültemeier, C.-A. Holst, V. Lohweg, M. Schöne, B. Jaster, M. Kohlhase, in: 2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (ETFA), IEEE, 2025, pp. 1–4.","chicago":"Bültemeier, Julian, Christoph-Alexander Holst, Volker Lohweg, Marvin Schöne, Bjarne Jaster, and Martin Kohlhase. “AI Workflow for Scarce Data: A Modular Approach to Optimise Processes.” In <i>2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (ETFA)</i>, 1–4. IEEE, 2025. <a href=\"https://doi.org/10.1109/ETFA65518.2025.11205664\">https://doi.org/10.1109/ETFA65518.2025.11205664</a>.","mla":"Bültemeier, Julian, et al. “AI Workflow for Scarce Data: A Modular Approach to Optimise Processes.” <i>2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (ETFA)</i>, IEEE, 2025, pp. 1–4, doi:<a href=\"https://doi.org/10.1109/ETFA65518.2025.11205664\">10.1109/ETFA65518.2025.11205664</a>.","ama":"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: <i>2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (ETFA)</i>. IEEE; 2025:1-4. doi:<a href=\"https://doi.org/10.1109/ETFA65518.2025.11205664\">10.1109/ETFA65518.2025.11205664</a>","ieee":"J. Bültemeier, C.-A. Holst, V. Lohweg, M. Schöne, B. Jaster, and M. Kohlhase, “AI Workflow for Scarce Data: A Modular Approach to Optimise Processes,” in <i>2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (ETFA)</i>, Porto, Portugal, 2025, pp. 1–4.","alphadin":"<span style=\"font-variant:small-caps;\">Bültemeier, Julian</span> ; <span style=\"font-variant:small-caps;\">Holst, Christoph-Alexander</span> ; <span style=\"font-variant:small-caps;\">Lohweg, Volker</span> ; <span style=\"font-variant:small-caps;\">Schöne, Marvin</span> ; <span style=\"font-variant:small-caps;\">Jaster, Bjarne</span> ; <span style=\"font-variant:small-caps;\">Kohlhase, Martin</span>: AI Workflow for Scarce Data: A Modular Approach to Optimise Processes. In: <i>2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (ETFA)</i> : IEEE, 2025, S. 1–4","apa":"Bültemeier, J., Holst, C.-A., Lohweg, V., Schöne, M., Jaster, B., &#38; Kohlhase, M. (2025). AI Workflow for Scarce Data: A Modular Approach to Optimise Processes. In <i>2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (ETFA)</i> (pp. 1–4). Porto, Portugal: IEEE. <a href=\"https://doi.org/10.1109/ETFA65518.2025.11205664\">https://doi.org/10.1109/ETFA65518.2025.11205664</a>","bibtex":"@inproceedings{Bültemeier_Holst_Lohweg_Schöne_Jaster_Kohlhase_2025, title={AI Workflow for Scarce Data: A Modular Approach to Optimise Processes}, DOI={<a href=\"https://doi.org/10.1109/ETFA65518.2025.11205664\">10.1109/ETFA65518.2025.11205664</a>}, booktitle={2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (ETFA)}, publisher={IEEE}, author={Bültemeier, Julian and Holst, Christoph-Alexander and Lohweg, Volker and Schöne, Marvin and Jaster, Bjarne and Kohlhase, Martin}, year={2025}, pages={1–4} }"},"author":[{"full_name":"Bültemeier, Julian","last_name":"Bültemeier","first_name":"Julian"},{"first_name":"Christoph-Alexander","full_name":"Holst, Christoph-Alexander","last_name":"Holst"},{"last_name":"Lohweg","full_name":"Lohweg, Volker","first_name":"Volker"},{"first_name":"Marvin","id":"218388","full_name":"Schöne, Marvin","last_name":"Schöne"},{"orcid":"0000-0002-8362-5369","full_name":"Jaster, Bjarne","last_name":"Jaster","first_name":"Bjarne","id":"252434","orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0002-8362-5369/work/196000534"},{"last_name":"Kohlhase","orcid":"0009-0002-9374-0720","full_name":"Kohlhase, Martin","first_name":"Martin","id":"226669","orcid_put_code_url":"https://api.orcid.org/v2.0/0009-0002-9374-0720/work/196000535"}],"conference":{"location":"Porto, Portugal","name":"2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (ETFA)"},"status":"public","publication_status":"published","publication":"2025 IEEE 30th International Conference on Emerging Technologies and Factory Automation (ETFA)","type":"conference","publication_identifier":{"eisbn":["979-8-3315-5383-8"]},"project":[{"_id":"f432a2ee-bceb-11ed-a251-a83585c5074d","name":"Institute for Data Science Solutions"}],"user_id":"252434","title":"AI Workflow for Scarce Data: A Modular Approach to Optimise Processes","date_created":"2025-11-04T14:01:05Z"},{"place":"Bielefeld","citation":{"chicago":"Schöne, Marvin, Bjarne Jaster, Julian Bültemeier, and Martin Kohlhase. “Informed Active Learning with Decision Trees to Balance Exploration and Exploitation.” In <i>Kongress KI@HSBI2025 Zukunft Im Fokus – Posterbeiträge</i>, edited by Institute for Data Science Solutions, 2:26–27. Schriftenreihe Des Institute for Data Science Solutions. Bielefeld: Hochschule Bielefeld, 2025. <a href=\"https://doi.org/10.60802/sidas.2025.2\">https://doi.org/10.60802/sidas.2025.2</a>.","short":"M. Schöne, B. Jaster, J. Bültemeier, M. Kohlhase, in: Institute for Data Science Solutions (Ed.), Kongress KI@HSBI2025 Zukunft Im Fokus – Posterbeiträge, Hochschule Bielefeld, Bielefeld, 2025, pp. 26–27.","ama":"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. <i>Kongress KI@HSBI2025 Zukunft Im Fokus – Posterbeiträge</i>. Vol 2. Schriftenreihe des Institute for Data Science Solutions. Bielefeld: Hochschule Bielefeld; 2025:26-27. doi:<a href=\"https://doi.org/10.60802/sidas.2025.2\">10.60802/sidas.2025.2</a>","mla":"Schöne, Marvin, et al. “Informed Active Learning with Decision Trees to Balance Exploration and Exploitation.” <i>Kongress KI@HSBI2025 Zukunft Im Fokus – Posterbeiträge</i>, edited by Institute for Data Science Solutions, vol. 2, Hochschule Bielefeld, 2025, pp. 26–27, doi:<a href=\"https://doi.org/10.60802/sidas.2025.2\">10.60802/sidas.2025.2</a>.","ieee":"M. Schöne, B. Jaster, J. Bültemeier, and M. Kohlhase, “Informed Active Learning with Decision Trees to Balance Exploration and Exploitation,” in <i>Kongress KI@HSBI2025 Zukunft im Fokus – Posterbeiträge</i>, vol. 2, Institute for Data Science Solutions, Ed. Bielefeld: Hochschule Bielefeld, 2025, pp. 26–27.","bibtex":"@inbook{Schöne_Jaster_Bültemeier_Kohlhase_2025, place={Bielefeld}, series={Schriftenreihe des Institute for Data Science Solutions}, title={Informed Active Learning with Decision Trees to Balance Exploration and Exploitation}, volume={2}, DOI={<a href=\"https://doi.org/10.60802/sidas.2025.2\">10.60802/sidas.2025.2</a>}, booktitle={Kongress KI@HSBI2025 Zukunft im Fokus – Posterbeiträge}, publisher={Hochschule Bielefeld}, author={Schöne, Marvin and Jaster, Bjarne and Bültemeier, Julian and Kohlhase, Martin}, editor={Institute for Data Science SolutionsEditor}, year={2025}, pages={26–27}, collection={Schriftenreihe des Institute for Data Science Solutions} }","apa":"Schöne, M., Jaster, B., Bültemeier, J., &#38; Kohlhase, M. (2025). Informed Active Learning with Decision Trees to Balance Exploration and Exploitation. In Institute for Data Science Solutions (Ed.), <i>Kongress KI@HSBI2025 Zukunft im Fokus – Posterbeiträge</i> (Vol. 2, pp. 26–27). Bielefeld: Hochschule Bielefeld. <a href=\"https://doi.org/10.60802/sidas.2025.2\">https://doi.org/10.60802/sidas.2025.2</a>","alphadin":"<span style=\"font-variant:small-caps;\">Schöne, Marvin</span> ; <span style=\"font-variant:small-caps;\">Jaster, Bjarne</span> ; <span style=\"font-variant:small-caps;\">Bültemeier, Julian</span> ; <span style=\"font-variant:small-caps;\">Kohlhase, Martin</span>: Informed Active Learning with Decision Trees to Balance Exploration and Exploitation. In: <span style=\"font-variant:small-caps;\">Institute for Data Science Solutions</span> (Hrsg.): <i>Kongress KI@HSBI2025 Zukunft im Fokus – Posterbeiträge</i>, <i>Schriftenreihe des Institute for Data Science Solutions</i>. Bd. 2. Bielefeld : Hochschule Bielefeld, 2025, S. 26–27"},"author":[{"last_name":"Schöne","full_name":"Schöne, Marvin","id":"218388","first_name":"Marvin"},{"orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0002-8362-5369/work/196032569","id":"252434","first_name":"Bjarne","full_name":"Jaster, Bjarne","orcid":"0000-0002-8362-5369","last_name":"Jaster"},{"first_name":"Julian","last_name":"Bültemeier","full_name":"Bültemeier, Julian"},{"first_name":"Martin","orcid_put_code_url":"https://api.orcid.org/v2.0/0009-0002-9374-0720/work/196032572","id":"226669","last_name":"Kohlhase","orcid":"0009-0002-9374-0720","full_name":"Kohlhase, Martin"}],"status":"public","intvolume":"         2","doi":"10.60802/sidas.2025.2","page":"26-27","publisher":"Hochschule Bielefeld","date_updated":"2026-03-17T15:29:28Z","year":"2025","_id":"6273","language":[{"iso":"eng"}],"title":"Informed Active Learning with Decision Trees to Balance Exploration and Exploitation","date_created":"2025-11-04T20:07:01Z","volume":2,"type":"book_chapter","project":[{"_id":"f432a2ee-bceb-11ed-a251-a83585c5074d","name":"Institute for Data Science Solutions"}],"oa":"1","user_id":"252434","main_file_link":[{"open_access":"1"}],"corporate_editor":["Institute for Data Science Solutions"],"series_title":"Schriftenreihe des Institute for Data Science Solutions","publication":"Kongress KI@HSBI2025 Zukunft im Fokus – Posterbeiträge","publication_status":"published"},{"language":[{"iso":"eng"}],"year":"2025","_id":"5905","conference":{"name":"2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx Companion)","location":"Trondheim, Norway","start_date":"2025-03-17","end_date":"2025-03-20"},"status":"public","citation":{"mla":"Jaster, Bjarne, and Martin Kohlhase. “Trust Issues in Active Learning and Their Impact on Real-World Applications.” <i>2025 IEEE Symposium on Trustworthy, Explainable and Responsible Computational Intelligence (CITREx Companion)</i>, edited by IEEE, IEEE, 2025, pp. 1–5, doi:<a href=\"https://doi.org/10.1109/CITRExCompanion65208.2025.10981492\">10.1109/CITRExCompanion65208.2025.10981492</a>.","ama":"Jaster B, Kohlhase M. 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Towards robust and domain agnostic reinforcement learning competitions. <i>arXiv</i>. 2021. doi:<a href=\"https://doi.org/10.48550/ARXIV.2106.03748\">10.48550/ARXIV.2106.03748</a>","chicago":"Guss, William Hebgen, Stephanie Milani, Nicholay Topin, Brandon Houghton, Sharada Mohanty, Andrew Melnik, Augustin Harter, et al. “Towards Robust and Domain Agnostic Reinforcement Learning Competitions.” <i>ArXiv</i>, 2021. <a href=\"https://doi.org/10.48550/ARXIV.2106.03748\">https://doi.org/10.48550/ARXIV.2106.03748</a>.","short":"W.H. Guss, S. Milani, N. Topin, B. Houghton, S. Mohanty, A. Melnik, A. Harter, B. Buschmaas, B. Jaster, C. Berganski, D. Heitkamp, M. Henning, H. Ritter, C. Wu, X. Hao, Y. Lu, H. Mao, Y. Mao, C. Wang, M. Opanowicz, A. Kanervisto, Y. Schraner, C. Scheller, X. Zhou, L. Liu, D. Nishio, T. Tsuneda, K. Ramanauskas, G. Juceviciute, ArXiv (2021).","alphadin":"<span style=\"font-variant:small-caps;\"><span style=\"font-variant:small-caps;\">Guss, William Hebgen</span> ; <span style=\"font-variant:small-caps;\">Milani, Stephanie</span> ; <span style=\"font-variant:small-caps;\">Topin, Nicholay</span> ; <span style=\"font-variant:small-caps;\">Houghton, Brandon</span> ; <span style=\"font-variant:small-caps;\">Mohanty, Sharada</span> ; <span style=\"font-variant:small-caps;\">Melnik, Andrew</span> ; <span style=\"font-variant:small-caps;\">Harter, Augustin</span> ; <span style=\"font-variant:small-caps;\">Buschmaas, Benoit</span> ; u. a.</span>: Towards robust and domain agnostic reinforcement learning competitions. In: <i>arXiv</i>, arXiv (2021)","bibtex":"@article{Guss_Milani_Topin_Houghton_Mohanty_Melnik_Harter_Buschmaas_Jaster_Berganski_et al._2021, title={Towards robust and domain agnostic reinforcement learning competitions}, DOI={<a href=\"https://doi.org/10.48550/ARXIV.2106.03748\">10.48550/ARXIV.2106.03748</a>}, journal={arXiv}, publisher={arXiv}, author={Guss, William Hebgen and Milani, Stephanie and Topin, Nicholay and Houghton, Brandon and Mohanty, Sharada and Melnik, Andrew and Harter, Augustin and Buschmaas, Benoit and Jaster, Bjarne and Berganski, Christoph and et al.}, year={2021} }","apa":"Guss, W. H., Milani, S., Topin, N., Houghton, B., Mohanty, S., Melnik, A., … Juceviciute, G. (2021). Towards robust and domain agnostic reinforcement learning competitions. <i>ArXiv</i>. <a href=\"https://doi.org/10.48550/ARXIV.2106.03748\">https://doi.org/10.48550/ARXIV.2106.03748</a>","ieee":"W. H. Guss <i>et al.</i>, “Towards robust and domain agnostic reinforcement learning competitions,” <i>arXiv</i>, 2021."}}]