[{"_id":"65182","user_id":"26032","department":[{"_id":"179"}],"language":[{"iso":"eng"}],"type":"journal_article","publication":"SSRN Electronic Journal","abstract":[{"text":"The aggregation of rating metrics in reputation systems is crucial for mitigating information overload by condensing customer rating distributions into singular valence scores. While platforms typically employ technical aggregation functions, such as the arithmetic mean to capture product quality, it remains unclear whether these functions align with customers' innate aggregation patterns. To address this knowledge gap, we designed a controlled economic decision experiment to elicit customers' aggregation principles by analyzing their product ranking decisions and contrasting these with various reference functions. Our findings indicate that, on average, customers aggregate rating information in accordance with the arithmetic mean. However, a granular analysis at the individual level reveals significant heterogeneity in aggregation behavior, with a substantial cluster exhibiting binary patterns that focus equally on negative (1-2 star) and positive (4-5 star) ratings. Additional clusters concentrate on negative feedback, particularly 1-star ratings or 1-2 star ratings collectively. Notably, these inherent aggregation patterns exhibit stability across variations in numerical information presentation and are not significantly influenced by individual characteristics, such as online shopping experience, risk attitudes, or demographics. These findings suggest that while the arithmetic mean captures average consumer behavior, platforms could benefit from offering customizable aggregation options to better cater to diverse user preferences for processing rating distributions. By doing so, platforms can enhance the effectiveness of their reputation systems and improve the overall quality of decision-making for consumers.","lang":"eng"}],"status":"public","date_updated":"2026-03-27T21:55:03Z","publisher":"Elsevier BV","date_created":"2026-03-27T16:21:55Z","author":[{"first_name":"Dirk","full_name":"van Straaten, Dirk","id":"10311","last_name":"van Straaten"},{"id":"26032","full_name":"Mir Djawadi, Behnud","last_name":"Mir Djawadi","orcid":"0000-0002-6271-5912","first_name":"Behnud"},{"full_name":"Melnikov, Vitalik","id":"58747","last_name":"Melnikov","first_name":"Vitalik"},{"id":"48129","full_name":"Hüllermeier, Eyke","last_name":"Hüllermeier","first_name":"Eyke"},{"first_name":"René","last_name":"Fahr","full_name":"Fahr, René","id":"111"}],"title":"Aggregation Processes in Customer Rating Systems - Insights from an Economic Decision Experiment","doi":"http://dx.doi.org/10.2139/ssrn.6201258","publication_status":"published","year":"2026","citation":{"short":"D. van Straaten, B. Mir Djawadi, V. Melnikov, E. Hüllermeier, R. Fahr, SSRN Electronic Journal (2026).","bibtex":"@article{van Straaten_Mir Djawadi_Melnikov_Hüllermeier_Fahr_2026, title={Aggregation Processes in Customer Rating Systems - Insights from an Economic Decision Experiment}, DOI={http://dx.doi.org/10.2139/ssrn.6201258}, journal={SSRN Electronic Journal}, publisher={Elsevier BV}, author={van Straaten, Dirk and Mir Djawadi, Behnud and Melnikov, Vitalik and Hüllermeier, Eyke and Fahr, René}, year={2026} }","mla":"van Straaten, Dirk, et al. “Aggregation Processes in Customer Rating Systems - Insights from an Economic Decision Experiment.” SSRN Electronic Journal, Elsevier BV, 2026, doi:http://dx.doi.org/10.2139/ssrn.6201258.","apa":"van Straaten, D., Mir Djawadi, B., Melnikov, V., Hüllermeier, E., & Fahr, R. (2026). Aggregation Processes in Customer Rating Systems - Insights from an Economic Decision Experiment. SSRN Electronic Journal. http://dx.doi.org/10.2139/ssrn.6201258","ieee":"D. van Straaten, B. Mir Djawadi, V. Melnikov, E. Hüllermeier, and R. Fahr, “Aggregation Processes in Customer Rating Systems - Insights from an Economic Decision Experiment,” SSRN Electronic Journal, 2026, doi: http://dx.doi.org/10.2139/ssrn.6201258.","chicago":"Straaten, Dirk van, Behnud Mir Djawadi, Vitalik Melnikov, Eyke Hüllermeier, and René Fahr. “Aggregation Processes in Customer Rating Systems - Insights from an Economic Decision Experiment.” SSRN Electronic Journal, 2026. http://dx.doi.org/10.2139/ssrn.6201258.","ama":"van Straaten D, Mir Djawadi B, Melnikov V, Hüllermeier E, Fahr R. Aggregation Processes in Customer Rating Systems - Insights from an Economic Decision Experiment. SSRN Electronic Journal. Published online 2026. doi:http://dx.doi.org/10.2139/ssrn.6201258"}},{"language":[{"iso":"eng"}],"external_id":{"arxiv":["2504.18483"]},"abstract":[{"lang":"eng","text":"The ability to generate explanations that are understood by explainees is the\r\nquintessence of explainable artificial intelligence. Since understanding\r\ndepends on the explainee's background and needs, recent research focused on\r\nco-constructive explanation dialogues, where an explainer continuously monitors\r\nthe explainee's understanding and adapts their explanations dynamically. We\r\ninvestigate the ability of large language models (LLMs) to engage as explainers\r\nin co-constructive explanation dialogues. In particular, we present a user\r\nstudy in which explainees interact with an LLM in two settings, one of which\r\ninvolves the LLM being instructed to explain a topic co-constructively. We\r\nevaluate the explainees' understanding before and after the dialogue, as well\r\nas their perception of the LLMs' co-constructive behavior. Our results suggest\r\nthat LLMs show some co-constructive behaviors, such as asking verification\r\nquestions, that foster the explainees' engagement and can improve understanding\r\nof a topic. However, their ability to effectively monitor the current\r\nunderstanding and scaffold the explanations accordingly remains limited."}],"publication":"Proceedings of the 26th Annual Meeting of the Special Interest Group on Discourse and Dialogue","title":"Investigating Co-Constructive Behavior of Large Language Models in Explanation Dialogues","publisher":"Association for Computational Linguistics","date_created":"2025-09-11T16:11:17Z","year":"2025","project":[{"name":"TRR 318: Project Area INF","_id":"118"},{"_id":"121","name":"TRR 318; TP B01: Ein dialogbasierter Ansatz zur Erklärung von Modellen des maschinellen Lernens"},{"_id":"127","name":"TRR 318; TP C04: Metaphern als Werkzeug des Erklärens"},{"_id":"122","name":"TRR 318 - Subproject B3"},{"name":"TRR 318 - Project Area Ö","_id":"119"},{"_id":"114","name":"TRR 318; TP A04: Integration des technischen Modells in das Partnermodell bei der Erklärung von digitalen Artefakten"}],"_id":"61234","user_id":"84035","department":[{"_id":"660"}],"status":"public","type":"conference","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2504.18483"}],"conference":{"name":"Annual Meeting of the Special Interest Group on Discourse and Dialogue"},"date_updated":"2025-09-12T09:50:48Z","oa":"1","author":[{"first_name":"Leandra","last_name":"Fichtel","full_name":"Fichtel, Leandra"},{"id":"84035","full_name":"Spliethöver, Maximilian","orcid":"0000-0003-4364-1409","last_name":"Spliethöver","first_name":"Maximilian"},{"first_name":"Eyke","full_name":"Hüllermeier, Eyke","id":"48129","last_name":"Hüllermeier"},{"full_name":"Jimenez, Patricia","id":"103339","last_name":"Jimenez","first_name":"Patricia"},{"first_name":"Nils","full_name":"Klowait, Nils","id":"98454","orcid":"0000-0002-7347-099X","last_name":"Klowait"},{"first_name":"Stefan","full_name":"Kopp, Stefan","last_name":"Kopp"},{"first_name":"Axel-Cyrille","last_name":"Ngonga Ngomo","full_name":"Ngonga Ngomo, Axel-Cyrille","id":"65716"},{"first_name":"Amelie","orcid":"0000-0001-5622-8248","last_name":"Robrecht","id":"91982","full_name":"Robrecht, Amelie"},{"id":"451","full_name":"Scharlau, Ingrid","orcid":"0000-0003-2364-9489","last_name":"Scharlau","first_name":"Ingrid"},{"full_name":"Terfloth, Lutz","id":"37320","last_name":"Terfloth","first_name":"Lutz"},{"first_name":"Anna-Lisa","full_name":"Vollmer, Anna-Lisa","id":"86589","last_name":"Vollmer"},{"first_name":"Henning","last_name":"Wachsmuth","full_name":"Wachsmuth, Henning","id":"3900"}],"place":"Avignon, France","citation":{"apa":"Fichtel, L., Spliethöver, M., Hüllermeier, E., Jimenez, P., Klowait, N., Kopp, S., Ngonga Ngomo, A.-C., Robrecht, A., Scharlau, I., Terfloth, L., Vollmer, A.-L., & Wachsmuth, H. (n.d.). Investigating Co-Constructive Behavior of Large Language Models in Explanation Dialogues. Proceedings of the 26th Annual Meeting of the Special Interest Group on Discourse and Dialogue. Annual Meeting of the Special Interest Group on Discourse and Dialogue.","bibtex":"@inproceedings{Fichtel_Spliethöver_Hüllermeier_Jimenez_Klowait_Kopp_Ngonga Ngomo_Robrecht_Scharlau_Terfloth_et al., place={Avignon, France}, title={Investigating Co-Constructive Behavior of Large Language Models in Explanation Dialogues}, booktitle={Proceedings of the 26th Annual Meeting of the Special Interest Group on Discourse and Dialogue}, publisher={Association for Computational Linguistics}, author={Fichtel, Leandra and Spliethöver, Maximilian and Hüllermeier, Eyke and Jimenez, Patricia and Klowait, Nils and Kopp, Stefan and Ngonga Ngomo, Axel-Cyrille and Robrecht, Amelie and Scharlau, Ingrid and Terfloth, Lutz and et al.} }","short":"L. Fichtel, M. Spliethöver, E. Hüllermeier, P. Jimenez, N. Klowait, S. Kopp, A.-C. Ngonga Ngomo, A. Robrecht, I. Scharlau, L. Terfloth, A.-L. Vollmer, H. Wachsmuth, in: Proceedings of the 26th Annual Meeting of the Special Interest Group on Discourse and Dialogue, Association for Computational Linguistics, Avignon, France, n.d.","mla":"Fichtel, Leandra, et al. “Investigating Co-Constructive Behavior of Large Language Models in Explanation Dialogues.” Proceedings of the 26th Annual Meeting of the Special Interest Group on Discourse and Dialogue, Association for Computational Linguistics.","chicago":"Fichtel, Leandra, Maximilian Spliethöver, Eyke Hüllermeier, Patricia Jimenez, Nils Klowait, Stefan Kopp, Axel-Cyrille Ngonga Ngomo, et al. “Investigating Co-Constructive Behavior of Large Language Models in Explanation Dialogues.” In Proceedings of the 26th Annual Meeting of the Special Interest Group on Discourse and Dialogue. Avignon, France: Association for Computational Linguistics, n.d.","ieee":"L. Fichtel et al., “Investigating Co-Constructive Behavior of Large Language Models in Explanation Dialogues,” presented at the Annual Meeting of the Special Interest Group on Discourse and Dialogue.","ama":"Fichtel L, Spliethöver M, Hüllermeier E, et al. Investigating Co-Constructive Behavior of Large Language Models in Explanation Dialogues. In: Proceedings of the 26th Annual Meeting of the Special Interest Group on Discourse and Dialogue. Association for Computational Linguistics."},"publication_status":"accepted","related_material":{"link":[{"relation":"software","url":"https://github.com/webis-de/sigdial25-co-constructive-llms"},{"url":"https://github.com/webis-de/sigdial25-co-constructive-llms-data","relation":"research_data"}]}},{"year":"2025","title":"Adaptive Prompting: Ad-hoc Prompt Composition for Social Bias Detection","date_created":"2025-05-10T12:37:45Z","publisher":"Association for Computational Linguistics","abstract":[{"lang":"eng","text":"Recent advances on instruction fine-tuning have led to the development of various prompting techniques for large language models, such as explicit reasoning steps. However, the success of techniques depends on various parameters, such as the task, language model, and context provided. Finding an effective prompt is, therefore, often a trial-and-error process. Most existing approaches to automatic prompting aim to optimize individual techniques instead of compositions of techniques and their dependence on the input. To fill this gap, we propose an adaptive prompting approach that predicts the optimal prompt composition ad-hoc for a given input. We apply our approach to social bias detection, a highly context-dependent task that requires semantic understanding. We evaluate it with three large language models on three datasets, comparing compositions to individual techniques and other baselines. The results underline the importance of finding an effective prompt composition. Our approach robustly ensures high detection performance, and is best in several settings. Moreover, first experiments on other tasks support its generalizability."}],"publication":"Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)","language":[{"iso":"eng"}],"page":"2421–2449","citation":{"apa":"Spliethöver, M., Knebler, T., Fumagalli, F., Muschalik, M., Hammer, B., Hüllermeier, E., & Wachsmuth, H. (2025). Adaptive Prompting: Ad-hoc Prompt Composition for Social Bias Detection. In L. Chiruzzo, A. Ritter, & L. Wang (Eds.), Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) (pp. 2421–2449). Association for Computational Linguistics.","short":"M. Spliethöver, T. Knebler, F. Fumagalli, M. Muschalik, B. Hammer, E. Hüllermeier, H. Wachsmuth, in: L. Chiruzzo, A. Ritter, L. Wang (Eds.), Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), Association for Computational Linguistics, Albuquerque, New Mexico, 2025, pp. 2421–2449.","bibtex":"@inproceedings{Spliethöver_Knebler_Fumagalli_Muschalik_Hammer_Hüllermeier_Wachsmuth_2025, place={Albuquerque, New Mexico}, title={Adaptive Prompting: Ad-hoc Prompt Composition for Social Bias Detection}, booktitle={Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)}, publisher={Association for Computational Linguistics}, author={Spliethöver, Maximilian and Knebler, Tim and Fumagalli, Fabian and Muschalik, Maximilian and Hammer, Barbara and Hüllermeier, Eyke and Wachsmuth, Henning}, editor={Chiruzzo, Luis and Ritter, Alan and Wang, Lu}, year={2025}, pages={2421–2449} }","mla":"Spliethöver, Maximilian, et al. “Adaptive Prompting: Ad-Hoc Prompt Composition for Social Bias Detection.” Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), edited by Luis Chiruzzo et al., Association for Computational Linguistics, 2025, pp. 2421–2449.","ieee":"M. Spliethöver et al., “Adaptive Prompting: Ad-hoc Prompt Composition for Social Bias Detection,” in Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2025, pp. 2421–2449.","chicago":"Spliethöver, Maximilian, Tim Knebler, Fabian Fumagalli, Maximilian Muschalik, Barbara Hammer, Eyke Hüllermeier, and Henning Wachsmuth. “Adaptive Prompting: Ad-Hoc Prompt Composition for Social Bias Detection.” In Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), edited by Luis Chiruzzo, Alan Ritter, and Lu Wang, 2421–2449. Albuquerque, New Mexico: Association for Computational Linguistics, 2025.","ama":"Spliethöver M, Knebler T, Fumagalli F, et al. Adaptive Prompting: Ad-hoc Prompt Composition for Social Bias Detection. In: Chiruzzo L, Ritter A, Wang L, eds. Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers). Association for Computational Linguistics; 2025:2421–2449."},"place":"Albuquerque, New Mexico","related_material":{"link":[{"relation":"software","url":"https://github.com/webis-de/naacl25-prompt-compositions"}]},"publication_identifier":{"isbn":["979-8-89176-189-6"]},"publication_status":"published","main_file_link":[{"url":"https://aclanthology.org/2025.naacl-long.122/","open_access":"1"}],"author":[{"first_name":"Maximilian","last_name":"Spliethöver","orcid":"0000-0003-4364-1409","id":"84035","full_name":"Spliethöver, Maximilian"},{"first_name":"Tim","last_name":"Knebler","full_name":"Knebler, Tim"},{"last_name":"Fumagalli","id":"93420","full_name":"Fumagalli, Fabian","first_name":"Fabian"},{"first_name":"Maximilian","last_name":"Muschalik","full_name":"Muschalik, Maximilian"},{"full_name":"Hammer, Barbara","last_name":"Hammer","first_name":"Barbara"},{"first_name":"Eyke","last_name":"Hüllermeier","full_name":"Hüllermeier, Eyke","id":"48129"},{"first_name":"Henning","last_name":"Wachsmuth","full_name":"Wachsmuth, Henning","id":"3900"}],"date_updated":"2025-09-12T09:51:30Z","oa":"1","status":"public","editor":[{"first_name":"Luis","last_name":"Chiruzzo","full_name":"Chiruzzo, Luis"},{"first_name":"Alan","last_name":"Ritter","full_name":"Ritter, Alan"},{"last_name":"Wang","full_name":"Wang, Lu","first_name":"Lu"}],"type":"conference","department":[{"_id":"660"}],"user_id":"84035","_id":"59856","project":[{"_id":"118","name":"TRR 318: Project Area INF"},{"_id":"126","name":"TRR 318 - Subproject C3"}]},{"doi":"10.1007/978-3-032-08327-2_6","title":"MSL: Multi-class Scoring Lists for Interpretable Incremental Decision-Making","author":[{"id":"39640","full_name":"Heid, Stefan","last_name":"Heid","orcid":"0000-0002-9461-7372","first_name":"Stefan"},{"full_name":"Kornowicz, Jaroslaw","id":"44029","last_name":"Kornowicz","orcid":"0000-0002-5654-9911","first_name":"Jaroslaw"},{"last_name":"Hanselle","full_name":"Hanselle, Jonas","first_name":"Jonas"},{"first_name":"Kirsten","id":"72497","full_name":"Thommes, Kirsten","last_name":"Thommes"},{"first_name":"Eyke","last_name":"Hüllermeier","id":"48129","full_name":"Hüllermeier, Eyke"}],"date_created":"2025-10-13T13:34:36Z","publisher":"Springer Nature Switzerland","date_updated":"2025-10-13T13:35:11Z","citation":{"ama":"Heid S, Kornowicz J, Hanselle J, Thommes K, Hüllermeier E. MSL: Multi-class Scoring Lists for Interpretable Incremental Decision-Making. In: Communications in Computer and Information Science. Springer Nature Switzerland; 2025. doi:10.1007/978-3-032-08327-2_6","chicago":"Heid, Stefan, Jaroslaw Kornowicz, Jonas Hanselle, Kirsten Thommes, and Eyke Hüllermeier. “MSL: Multi-Class Scoring Lists for Interpretable Incremental Decision-Making.” In Communications in Computer and Information Science. Cham: Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-032-08327-2_6.","ieee":"S. Heid, J. Kornowicz, J. Hanselle, K. Thommes, and E. Hüllermeier, “MSL: Multi-class Scoring Lists for Interpretable Incremental Decision-Making,” in Communications in Computer and Information Science, Cham: Springer Nature Switzerland, 2025.","short":"S. Heid, J. Kornowicz, J. Hanselle, K. Thommes, E. Hüllermeier, in: Communications in Computer and Information Science, Springer Nature Switzerland, Cham, 2025.","mla":"Heid, Stefan, et al. “MSL: Multi-Class Scoring Lists for Interpretable Incremental Decision-Making.” Communications in Computer and Information Science, Springer Nature Switzerland, 2025, doi:10.1007/978-3-032-08327-2_6.","bibtex":"@inbook{Heid_Kornowicz_Hanselle_Thommes_Hüllermeier_2025, place={Cham}, title={MSL: Multi-class Scoring Lists for Interpretable Incremental Decision-Making}, DOI={10.1007/978-3-032-08327-2_6}, booktitle={Communications in Computer and Information Science}, publisher={Springer Nature Switzerland}, author={Heid, Stefan and Kornowicz, Jaroslaw and Hanselle, Jonas and Thommes, Kirsten and Hüllermeier, Eyke}, year={2025} }","apa":"Heid, S., Kornowicz, J., Hanselle, J., Thommes, K., & Hüllermeier, E. (2025). MSL: Multi-class Scoring Lists for Interpretable Incremental Decision-Making. In Communications in Computer and Information Science. Springer Nature Switzerland. https://doi.org/10.1007/978-3-032-08327-2_6"},"place":"Cham","year":"2025","publication_identifier":{"isbn":["9783032083265","9783032083272"],"issn":["1865-0929","1865-0937"]},"publication_status":"published","language":[{"iso":"eng"}],"department":[{"_id":"178"},{"_id":"184"}],"user_id":"72497","_id":"61820","project":[{"name":"TRR 318 - Subproject C2","_id":"125"}],"status":"public","abstract":[{"text":"Abstract\r\n A scoring list is a sequence of simple decision models, where features are incrementally evaluated and scores of satisfied features are summed to be used for threshold-based decisions or for calculating class probabilities. In this paper, we introduce a new multi-class variant and compare it against previously introduced binary classification variants for incremental decisions, as well as multi-class variants for classical decision-making using all features. Furthermore, we introduce a new multi-class dataset to assess collaborative human-machine decision-making, which is suitable for user studies with non-expert participants. We demonstrate the usefulness of our approach by evaluating predictive performance and compared to the performance of participants without AI help.","lang":"eng"}],"publication":"Communications in Computer and Information Science","type":"book_chapter"},{"department":[{"_id":"660"}],"user_id":"72497","_id":"54911","project":[{"_id":"125","name":"TRR 318 - C2: TRR 318 - Subproject C2"}],"language":[{"iso":"eng"}],"article_number":"109190","publication":"International Journal of Approximate Reasoning","type":"journal_article","status":"public","volume":171,"date_created":"2024-06-26T14:28:07Z","author":[{"id":"39640","full_name":"Heid, Stefan","orcid":"0000-0002-9461-7372","last_name":"Heid","first_name":"Stefan"},{"first_name":"Jonas Manuel","full_name":"Hanselle, Jonas Manuel","id":"43980","orcid":"0000-0002-1231-4985","last_name":"Hanselle"},{"full_name":"Fürnkranz, Johannes","last_name":"Fürnkranz","first_name":"Johannes"},{"last_name":"Hüllermeier","id":"48129","full_name":"Hüllermeier, Eyke","first_name":"Eyke"}],"publisher":"Elsevier BV","date_updated":"2024-06-26T14:28:47Z","doi":"10.1016/j.ijar.2024.109190","title":"Learning decision catalogues for situated decision making: The case of scoring systems","publication_identifier":{"issn":["0888-613X"]},"publication_status":"published","intvolume":" 171","citation":{"apa":"Heid, S., Hanselle, J. M., Fürnkranz, J., & Hüllermeier, E. (2024). Learning decision catalogues for situated decision making: The case of scoring systems. International Journal of Approximate Reasoning, 171, Article 109190. https://doi.org/10.1016/j.ijar.2024.109190","mla":"Heid, Stefan, et al. “Learning Decision Catalogues for Situated Decision Making: The Case of Scoring Systems.” International Journal of Approximate Reasoning, vol. 171, 109190, Elsevier BV, 2024, doi:10.1016/j.ijar.2024.109190.","bibtex":"@article{Heid_Hanselle_Fürnkranz_Hüllermeier_2024, title={Learning decision catalogues for situated decision making: The case of scoring systems}, volume={171}, DOI={10.1016/j.ijar.2024.109190}, number={109190}, journal={International Journal of Approximate Reasoning}, publisher={Elsevier BV}, author={Heid, Stefan and Hanselle, Jonas Manuel and Fürnkranz, Johannes and Hüllermeier, Eyke}, year={2024} }","short":"S. Heid, J.M. Hanselle, J. Fürnkranz, E. Hüllermeier, International Journal of Approximate Reasoning 171 (2024).","chicago":"Heid, Stefan, Jonas Manuel Hanselle, Johannes Fürnkranz, and Eyke Hüllermeier. “Learning Decision Catalogues for Situated Decision Making: The Case of Scoring Systems.” International Journal of Approximate Reasoning 171 (2024). https://doi.org/10.1016/j.ijar.2024.109190.","ieee":"S. Heid, J. M. Hanselle, J. Fürnkranz, and E. Hüllermeier, “Learning decision catalogues for situated decision making: The case of scoring systems,” International Journal of Approximate Reasoning, vol. 171, Art. no. 109190, 2024, doi: 10.1016/j.ijar.2024.109190.","ama":"Heid S, Hanselle JM, Fürnkranz J, Hüllermeier E. Learning decision catalogues for situated decision making: The case of scoring systems. International Journal of Approximate Reasoning. 2024;171. doi:10.1016/j.ijar.2024.109190"},"year":"2024"},{"status":"public","publication":"International Journal of Approximate Reasoning","type":"journal_article","article_number":"109190","language":[{"iso":"eng"}],"_id":"54910","department":[{"_id":"178"},{"_id":"184"}],"user_id":"72497","year":"2024","intvolume":" 171","citation":{"bibtex":"@article{Heid_Hanselle_Fürnkranz_Hüllermeier_2024, title={Learning decision catalogues for situated decision making: The case of scoring systems}, volume={171}, DOI={10.1016/j.ijar.2024.109190}, number={109190}, journal={International Journal of Approximate Reasoning}, publisher={Elsevier BV}, author={Heid, Stefan and Hanselle, Jonas Manuel and Fürnkranz, Johannes and Hüllermeier, Eyke}, year={2024} }","short":"S. Heid, J.M. Hanselle, J. Fürnkranz, E. Hüllermeier, International Journal of Approximate Reasoning 171 (2024).","mla":"Heid, Stefan, et al. “Learning Decision Catalogues for Situated Decision Making: The Case of Scoring Systems.” International Journal of Approximate Reasoning, vol. 171, 109190, Elsevier BV, 2024, doi:10.1016/j.ijar.2024.109190.","apa":"Heid, S., Hanselle, J. M., Fürnkranz, J., & Hüllermeier, E. (2024). Learning decision catalogues for situated decision making: The case of scoring systems. International Journal of Approximate Reasoning, 171, Article 109190. https://doi.org/10.1016/j.ijar.2024.109190","ieee":"S. Heid, J. M. Hanselle, J. Fürnkranz, and E. Hüllermeier, “Learning decision catalogues for situated decision making: The case of scoring systems,” International Journal of Approximate Reasoning, vol. 171, Art. no. 109190, 2024, doi: 10.1016/j.ijar.2024.109190.","chicago":"Heid, Stefan, Jonas Manuel Hanselle, Johannes Fürnkranz, and Eyke Hüllermeier. “Learning Decision Catalogues for Situated Decision Making: The Case of Scoring Systems.” International Journal of Approximate Reasoning 171 (2024). https://doi.org/10.1016/j.ijar.2024.109190.","ama":"Heid S, Hanselle JM, Fürnkranz J, Hüllermeier E. Learning decision catalogues for situated decision making: The case of scoring systems. International Journal of Approximate Reasoning. 2024;171. doi:10.1016/j.ijar.2024.109190"},"publication_identifier":{"issn":["0888-613X"]},"publication_status":"published","title":"Learning decision catalogues for situated decision making: The case of scoring systems","doi":"10.1016/j.ijar.2024.109190","date_updated":"2024-06-26T14:27:42Z","publisher":"Elsevier BV","volume":171,"author":[{"first_name":"Stefan","last_name":"Heid","orcid":"0000-0002-9461-7372","id":"39640","full_name":"Heid, Stefan"},{"first_name":"Jonas Manuel","orcid":"0000-0002-1231-4985","last_name":"Hanselle","full_name":"Hanselle, Jonas Manuel","id":"43980"},{"last_name":"Fürnkranz","full_name":"Fürnkranz, Johannes","first_name":"Johannes"},{"first_name":"Eyke","last_name":"Hüllermeier","id":"48129","full_name":"Hüllermeier, Eyke"}],"date_created":"2024-06-26T14:27:27Z"},{"year":"2024","citation":{"ama":"Heid S, Hanselle JM, Fürnkranz J, Hüllermeier E. Learning decision catalogues for situated decision making: The case of scoring systems. International Journal of Approximate Reasoning. 2024;171. doi:10.1016/j.ijar.2024.109190","ieee":"S. Heid, J. M. Hanselle, J. Fürnkranz, and E. Hüllermeier, “Learning decision catalogues for situated decision making: The case of scoring systems,” International Journal of Approximate Reasoning, vol. 171, Art. no. 109190, 2024, doi: 10.1016/j.ijar.2024.109190.","chicago":"Heid, Stefan, Jonas Manuel Hanselle, Johannes Fürnkranz, and Eyke Hüllermeier. “Learning Decision Catalogues for Situated Decision Making: The Case of Scoring Systems.” International Journal of Approximate Reasoning 171 (2024). https://doi.org/10.1016/j.ijar.2024.109190.","mla":"Heid, Stefan, et al. “Learning Decision Catalogues for Situated Decision Making: The Case of Scoring Systems.” International Journal of Approximate Reasoning, vol. 171, 109190, Elsevier BV, 2024, doi:10.1016/j.ijar.2024.109190.","short":"S. Heid, J.M. Hanselle, J. Fürnkranz, E. Hüllermeier, International Journal of Approximate Reasoning 171 (2024).","bibtex":"@article{Heid_Hanselle_Fürnkranz_Hüllermeier_2024, title={Learning decision catalogues for situated decision making: The case of scoring systems}, volume={171}, DOI={10.1016/j.ijar.2024.109190}, number={109190}, journal={International Journal of Approximate Reasoning}, publisher={Elsevier BV}, author={Heid, Stefan and Hanselle, Jonas Manuel and Fürnkranz, Johannes and Hüllermeier, Eyke}, year={2024} }","apa":"Heid, S., Hanselle, J. M., Fürnkranz, J., & Hüllermeier, E. (2024). Learning decision catalogues for situated decision making: The case of scoring systems. International Journal of Approximate Reasoning, 171, Article 109190. https://doi.org/10.1016/j.ijar.2024.109190"},"intvolume":" 171","publication_status":"published","publication_identifier":{"issn":["0888-613X"]},"title":"Learning decision catalogues for situated decision making: The case of scoring systems","doi":"10.1016/j.ijar.2024.109190","publisher":"Elsevier BV","date_updated":"2024-11-20T09:44:54Z","author":[{"id":"39640","full_name":"Heid, Stefan","last_name":"Heid","orcid":"0000-0002-9461-7372","first_name":"Stefan"},{"full_name":"Hanselle, Jonas Manuel","id":"43980","last_name":"Hanselle","orcid":"0000-0002-1231-4985","first_name":"Jonas Manuel"},{"first_name":"Johannes","full_name":"Fürnkranz, Johannes","last_name":"Fürnkranz"},{"full_name":"Hüllermeier, Eyke","id":"48129","last_name":"Hüllermeier","first_name":"Eyke"}],"date_created":"2024-06-26T14:19:19Z","volume":171,"status":"public","type":"journal_article","publication":"International Journal of Approximate Reasoning","article_number":"109190","language":[{"iso":"eng"}],"project":[{"name":"TRR 318 - C2: TRR 318 - Subproject C2","_id":"125"}],"_id":"54907","user_id":"72497","department":[{"_id":"660"}]},{"language":[{"iso":"eng"}],"user_id":"72497","department":[{"_id":"178"},{"_id":"184"}],"project":[{"name":"TRR 318 - C2: TRR 318 - Subproject C2","_id":"125"}],"_id":"57645","status":"public","type":"conference","publication":"PROCEEDINGS 34. WORKSHOP COMPUTATIONAL INTELLIGENCE","title":"Human-AI Co-Construction of Interpretable Predictive Models: The Case of Scoring Systems","date_created":"2024-12-09T08:05:54Z","author":[{"id":"39640","full_name":"Heid, Stefan","last_name":"Heid","orcid":"0000-0002-9461-7372","first_name":"Stefan"},{"first_name":"Jaroslaw","orcid":"0000-0002-5654-9911","last_name":"Kornowicz","id":"44029","full_name":"Kornowicz, Jaroslaw"},{"orcid":"0000-0002-1231-4985","last_name":"Hanselle","full_name":"Hanselle, Jonas Manuel","id":"43980","first_name":"Jonas Manuel"},{"last_name":"Hüllermeier","full_name":"Hüllermeier, Eyke","id":"48129","first_name":"Eyke"},{"full_name":"Thommes, Kirsten","id":"72497","last_name":"Thommes","first_name":"Kirsten"}],"volume":21,"date_updated":"2024-12-09T08:06:37Z","citation":{"chicago":"Heid, Stefan, Jaroslaw Kornowicz, Jonas Manuel Hanselle, Eyke Hüllermeier, and Kirsten Thommes. “Human-AI Co-Construction of Interpretable Predictive Models: The Case of Scoring Systems.” In PROCEEDINGS 34. WORKSHOP COMPUTATIONAL INTELLIGENCE, 21:233, 2024.","ieee":"S. Heid, J. Kornowicz, J. M. Hanselle, E. Hüllermeier, and K. Thommes, “Human-AI Co-Construction of Interpretable Predictive Models: The Case of Scoring Systems,” in PROCEEDINGS 34. WORKSHOP COMPUTATIONAL INTELLIGENCE, 2024, vol. 21, p. 233.","ama":"Heid S, Kornowicz J, Hanselle JM, Hüllermeier E, Thommes K. Human-AI Co-Construction of Interpretable Predictive Models: The Case of Scoring Systems. In: PROCEEDINGS 34. WORKSHOP COMPUTATIONAL INTELLIGENCE. Vol 21. ; 2024:233.","apa":"Heid, S., Kornowicz, J., Hanselle, J. M., Hüllermeier, E., & Thommes, K. (2024). Human-AI Co-Construction of Interpretable Predictive Models: The Case of Scoring Systems. PROCEEDINGS 34. WORKSHOP COMPUTATIONAL INTELLIGENCE, 21, 233.","short":"S. Heid, J. Kornowicz, J.M. Hanselle, E. Hüllermeier, K. Thommes, in: PROCEEDINGS 34. WORKSHOP COMPUTATIONAL INTELLIGENCE, 2024, p. 233.","mla":"Heid, Stefan, et al. “Human-AI Co-Construction of Interpretable Predictive Models: The Case of Scoring Systems.” PROCEEDINGS 34. WORKSHOP COMPUTATIONAL INTELLIGENCE, vol. 21, 2024, p. 233.","bibtex":"@inproceedings{Heid_Kornowicz_Hanselle_Hüllermeier_Thommes_2024, title={Human-AI Co-Construction of Interpretable Predictive Models: The Case of Scoring Systems}, volume={21}, booktitle={PROCEEDINGS 34. WORKSHOP COMPUTATIONAL INTELLIGENCE}, author={Heid, Stefan and Kornowicz, Jaroslaw and Hanselle, Jonas Manuel and Hüllermeier, Eyke and Thommes, Kirsten}, year={2024}, pages={233} }"},"intvolume":" 21","page":"233","year":"2024"},{"abstract":[{"lang":"eng","text":"This paper investigates the remaining useful lifetime (RUL) estimation of bearings under dynamic, i.e., time-varying, operating conditions (OC). Unlike conventional studies that assume constant OC in bearing accelerated life tests, we introduce a dataset with time-varying OC during run-to-failure experiments, simulating real-world scenarios. We explore data-driven approaches to identify the transition point from a healthy to an unhealthy state and estimate the RUL. Additionally, we examine strategies for integrating OC information to enhance RUL estimations. These methodologies are evaluated through numerical experiments using various machine learning algorithms."}],"publication":"PHM Society European Conference","language":[{"iso":"eng"}],"year":"2024","quality_controlled":"1","issue":"1","title":"Remaining Useful Lifetime Estimation of Bearings Operating under Time-Varying Conditions","publisher":"PHM Society","date_created":"2024-08-19T07:41:32Z","status":"public","type":"conference","article_number":"9","_id":"55631","user_id":"9557","department":[{"_id":"151"}],"citation":{"short":"A. Javanmardi, O.K. Aimiyekagbon, A. Bender, J.K. Kimotho, W. Sextro, E. Hüllermeier, in: PHM Society European Conference, PHM Society, 2024.","bibtex":"@inproceedings{Javanmardi_Aimiyekagbon_Bender_Kimotho_Sextro_Hüllermeier_2024, title={Remaining Useful Lifetime Estimation of Bearings Operating under Time-Varying Conditions}, volume={8}, DOI={10.36001/phme.2024.v8i1.4101}, number={19}, booktitle={PHM Society European Conference}, publisher={PHM Society}, author={Javanmardi, Alireza and Aimiyekagbon, Osarenren Kennedy and Bender, Amelie and Kimotho, James Kuria and Sextro, Walter and Hüllermeier, Eyke}, year={2024} }","mla":"Javanmardi, Alireza, et al. “Remaining Useful Lifetime Estimation of Bearings Operating under Time-Varying Conditions.” PHM Society European Conference, vol. 8, no. 1, 9, PHM Society, 2024, doi:10.36001/phme.2024.v8i1.4101.","apa":"Javanmardi, A., Aimiyekagbon, O. K., Bender, A., Kimotho, J. K., Sextro, W., & Hüllermeier, E. (2024). Remaining Useful Lifetime Estimation of Bearings Operating under Time-Varying Conditions. PHM Society European Conference, 8(1), Article 9. https://doi.org/10.36001/phme.2024.v8i1.4101","ieee":"A. Javanmardi, O. K. Aimiyekagbon, A. Bender, J. K. Kimotho, W. Sextro, and E. Hüllermeier, “Remaining Useful Lifetime Estimation of Bearings Operating under Time-Varying Conditions,” in PHM Society European Conference, Prague, Czech Republic, 2024, vol. 8, no. 1, doi: 10.36001/phme.2024.v8i1.4101.","chicago":"Javanmardi, Alireza, Osarenren Kennedy Aimiyekagbon, Amelie Bender, James Kuria Kimotho, Walter Sextro, and Eyke Hüllermeier. “Remaining Useful Lifetime Estimation of Bearings Operating under Time-Varying Conditions.” In PHM Society European Conference, Vol. 8. PHM Society, 2024. https://doi.org/10.36001/phme.2024.v8i1.4101.","ama":"Javanmardi A, Aimiyekagbon OK, Bender A, Kimotho JK, Sextro W, Hüllermeier E. Remaining Useful Lifetime Estimation of Bearings Operating under Time-Varying Conditions. In: PHM Society European Conference. Vol 8. PHM Society; 2024. doi:10.36001/phme.2024.v8i1.4101"},"intvolume":" 8","publication_status":"published","publication_identifier":{"isbn":["978-1-936263-40-0"]},"conference":{"name":"8th European Conference of the Prognostics and Health Management Society 2024","start_date":"2024-07-03","end_date":"2024-07-05","location":"Prague, Czech Republic"},"doi":"10.36001/phme.2024.v8i1.4101","date_updated":"2025-02-10T10:37:52Z","author":[{"full_name":"Javanmardi, Alireza","last_name":"Javanmardi","first_name":"Alireza"},{"full_name":"Aimiyekagbon, Osarenren Kennedy","id":"9557","last_name":"Aimiyekagbon","first_name":"Osarenren Kennedy"},{"id":"54290","full_name":"Bender, Amelie","last_name":"Bender","first_name":"Amelie"},{"full_name":"Kimotho, James Kuria","last_name":"Kimotho","first_name":"James Kuria"},{"first_name":"Walter","last_name":"Sextro","id":"21220","full_name":"Sextro, Walter"},{"first_name":"Eyke","last_name":"Hüllermeier","full_name":"Hüllermeier, Eyke","id":"48129"}],"volume":8},{"abstract":[{"text":"While shallow decision trees may be interpretable, larger ensemble models like gradient-boosted trees, which often set the state of the art in machine learning problems involving tabular data, still remain black box models. As a remedy, the Shapley value (SV) is a well-known concept in explainable artificial intelligence (XAI) research for quantifying additive feature attributions of predictions. The model-specific TreeSHAP methodology solves the exponential complexity for retrieving exact SVs from tree-based models. Expanding beyond individual feature attribution, Shapley interactions reveal the impact of intricate feature interactions of any order. In this work, we present TreeSHAP-IQ, an efficient method to compute any-order additive Shapley interactions for predictions of tree-based models. TreeSHAP-IQ is supported by a mathematical framework that exploits polynomial arithmetic to compute the interaction scores in a single recursive traversal of the tree, akin to Linear TreeSHAP. We apply TreeSHAP-IQ on state-of-the-art tree ensembles and explore interactions on well-established benchmark datasets.","lang":"eng"}],"status":"public","type":"conference","publication":"Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)","keyword":["Explainable Artificial Intelligence"],"language":[{"iso":"eng"}],"project":[{"name":"TRR 318 - C3: TRR 318 - Subproject C3","_id":"126"},{"name":"TRR 318: TRR 318 - Erklärbarkeit konstruieren","_id":"109"},{"_id":"117","name":"TRR 318 - C: TRR 318 - Project Area C"}],"_id":"53073","user_id":"93420","department":[{"_id":"660"}],"year":"2024","citation":{"ama":"Muschalik M, Fumagalli F, Hammer B, Huellermeier E. Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI). Vol 38. ; 2024:14388-14396. doi:10.1609/aaai.v38i13.29352","chicago":"Muschalik, Maximilian, Fabian Fumagalli, Barbara Hammer, and Eyke Huellermeier. “Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles.” In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 38:14388–96, 2024. https://doi.org/10.1609/aaai.v38i13.29352.","ieee":"M. Muschalik, F. Fumagalli, B. Hammer, and E. Huellermeier, “Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles,” in Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024, vol. 38, no. 13, pp. 14388–14396, doi: 10.1609/aaai.v38i13.29352.","apa":"Muschalik, M., Fumagalli, F., Hammer, B., & Huellermeier, E. (2024). Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 38(13), 14388–14396. https://doi.org/10.1609/aaai.v38i13.29352","bibtex":"@inproceedings{Muschalik_Fumagalli_Hammer_Huellermeier_2024, title={Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles}, volume={38}, DOI={10.1609/aaai.v38i13.29352}, number={13}, booktitle={Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)}, author={Muschalik, Maximilian and Fumagalli, Fabian and Hammer, Barbara and Huellermeier, Eyke}, year={2024}, pages={14388–14396} }","mla":"Muschalik, Maximilian, et al. “Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles.” Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), vol. 38, no. 13, 2024, pp. 14388–96, doi:10.1609/aaai.v38i13.29352.","short":"M. Muschalik, F. Fumagalli, B. Hammer, E. Huellermeier, in: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2024, pp. 14388–14396."},"page":"14388-14396","intvolume":" 38","publication_status":"published","publication_identifier":{"issn":["2374-3468","2159-5399"]},"issue":"13","title":"Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles","doi":"10.1609/aaai.v38i13.29352","date_updated":"2025-09-11T16:20:11Z","date_created":"2024-03-27T14:50:04Z","author":[{"last_name":"Muschalik","full_name":"Muschalik, Maximilian","first_name":"Maximilian"},{"last_name":"Fumagalli","id":"93420","full_name":"Fumagalli, Fabian","first_name":"Fabian"},{"first_name":"Barbara","full_name":"Hammer, Barbara","last_name":"Hammer"},{"id":"48129","full_name":"Huellermeier, Eyke","last_name":"Huellermeier","first_name":"Eyke"}],"volume":38},{"language":[{"iso":"eng"}],"_id":"55311","project":[{"name":"TRR 318: TRR 318 - Erklärbarkeit konstruieren","_id":"109"},{"_id":"117","name":"TRR 318 - C: TRR 318 - Project Area C"},{"name":"TRR 318 - C3: TRR 318 - Subproject C3","_id":"126"}],"department":[{"_id":"660"}],"series_title":"Proceedings of Machine Learning Research","user_id":"93420","abstract":[{"text":"Addressing the limitations of individual attribution scores via the Shapley value (SV), the field of explainable AI (XAI) has recently explored intricate interactions of features or data points. In particular, extensions of the SV, such as the Shapley Interaction Index (SII), have been proposed as a measure to still benefit from the axiomatic basis of the SV. However, similar to the SV, their exact computation remains computationally prohibitive. Hence, we propose with SVARM-IQ a sampling-based approach to efficiently approximate Shapley-based interaction indices of any order. SVARM-IQ can be applied to a broad class of interaction indices, including the SII, by leveraging a novel stratified representation. We provide non-asymptotic theoretical guarantees on its approximation quality and empirically demonstrate that SVARM-IQ achieves state-of-the-art estimation results in practical XAI scenarios on different model classes and application domains.","lang":"eng"}],"status":"public","publication":"Proceedings of The 27th International Conference on Artificial Intelligence and Statistics (AISTATS)","type":"conference","title":"SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification","publisher":"PMLR","date_updated":"2025-09-11T16:22:30Z","volume":238,"date_created":"2024-07-18T09:39:14Z","author":[{"last_name":"Kolpaczki","full_name":"Kolpaczki, Patrick","first_name":"Patrick"},{"last_name":"Muschalik","full_name":"Muschalik, Maximilian","first_name":"Maximilian"},{"id":"93420","full_name":"Fumagalli, Fabian","last_name":"Fumagalli","first_name":"Fabian"},{"full_name":"Hammer, Barbara","last_name":"Hammer","first_name":"Barbara"},{"last_name":"Huellermeier","full_name":"Huellermeier, Eyke","id":"48129","first_name":"Eyke"}],"year":"2024","page":"3520–3528","intvolume":" 238","citation":{"ieee":"P. Kolpaczki, M. Muschalik, F. Fumagalli, B. Hammer, and E. Huellermeier, “SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification,” in Proceedings of The 27th International Conference on Artificial Intelligence and Statistics (AISTATS), 2024, vol. 238, pp. 3520–3528.","chicago":"Kolpaczki, Patrick, Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, and Eyke Huellermeier. “SVARM-IQ: Efficient Approximation of Any-Order Shapley Interactions through Stratification.” In Proceedings of The 27th International Conference on Artificial Intelligence and Statistics (AISTATS), 238:3520–3528. Proceedings of Machine Learning Research. PMLR, 2024.","ama":"Kolpaczki P, Muschalik M, Fumagalli F, Hammer B, Huellermeier E. SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification. In: Proceedings of The 27th International Conference on Artificial Intelligence and Statistics (AISTATS). Vol 238. Proceedings of Machine Learning Research. PMLR; 2024:3520–3528.","apa":"Kolpaczki, P., Muschalik, M., Fumagalli, F., Hammer, B., & Huellermeier, E. (2024). SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification. Proceedings of The 27th International Conference on Artificial Intelligence and Statistics (AISTATS), 238, 3520–3528.","bibtex":"@inproceedings{Kolpaczki_Muschalik_Fumagalli_Hammer_Huellermeier_2024, series={Proceedings of Machine Learning Research}, title={SVARM-IQ: Efficient Approximation of Any-order Shapley Interactions through Stratification}, volume={238}, booktitle={Proceedings of The 27th International Conference on Artificial Intelligence and Statistics (AISTATS)}, publisher={PMLR}, author={Kolpaczki, Patrick and Muschalik, Maximilian and Fumagalli, Fabian and Hammer, Barbara and Huellermeier, Eyke}, year={2024}, pages={3520–3528}, collection={Proceedings of Machine Learning Research} }","short":"P. Kolpaczki, M. Muschalik, F. Fumagalli, B. Hammer, E. Huellermeier, in: Proceedings of The 27th International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR, 2024, pp. 3520–3528.","mla":"Kolpaczki, Patrick, et al. “SVARM-IQ: Efficient Approximation of Any-Order Shapley Interactions through Stratification.” Proceedings of The 27th International Conference on Artificial Intelligence and Statistics (AISTATS), vol. 238, PMLR, 2024, pp. 3520–3528."}},{"user_id":"93420","department":[{"_id":"660"}],"project":[{"name":"TRR 318 - Project Area C","_id":"117"},{"_id":"126","name":"TRR 318 - Subproject C3"},{"_id":"109","name":"TRR 318: Erklärbarkeit konstruieren"}],"_id":"61228","language":[{"iso":"eng"}],"type":"conference","publication":"Advances in Neural Information Processing Systems (NeurIPS)","status":"public","author":[{"last_name":"Muschalik","full_name":"Muschalik, Maximilian","first_name":"Maximilian"},{"first_name":"Hubert","last_name":"Baniecki","full_name":"Baniecki, Hubert"},{"last_name":"Fumagalli","id":"93420","full_name":"Fumagalli, Fabian","first_name":"Fabian"},{"first_name":"Patrick","last_name":"Kolpaczki","full_name":"Kolpaczki, Patrick"},{"first_name":"Barbara","full_name":"Hammer, Barbara","last_name":"Hammer"},{"first_name":"Eyke","full_name":"Huellermeier, Eyke","id":"48129","last_name":"Huellermeier"}],"date_created":"2025-09-11T15:39:01Z","volume":37,"date_updated":"2025-09-11T16:17:35Z","title":"shapiq: Shapley interactions for machine learning","citation":{"chicago":"Muschalik, Maximilian, Hubert Baniecki, Fabian Fumagalli, Patrick Kolpaczki, Barbara Hammer, and Eyke Huellermeier. “Shapiq: Shapley Interactions for Machine Learning.” In Advances in Neural Information Processing Systems (NeurIPS), 37:130324–130357, 2024.","ieee":"M. Muschalik, H. Baniecki, F. Fumagalli, P. Kolpaczki, B. Hammer, and E. Huellermeier, “shapiq: Shapley interactions for machine learning,” in Advances in Neural Information Processing Systems (NeurIPS), 2024, vol. 37, pp. 130324–130357.","ama":"Muschalik M, Baniecki H, Fumagalli F, Kolpaczki P, Hammer B, Huellermeier E. shapiq: Shapley interactions for machine learning. In: Advances in Neural Information Processing Systems (NeurIPS). Vol 37. ; 2024:130324–130357.","apa":"Muschalik, M., Baniecki, H., Fumagalli, F., Kolpaczki, P., Hammer, B., & Huellermeier, E. (2024). shapiq: Shapley interactions for machine learning. Advances in Neural Information Processing Systems (NeurIPS), 37, 130324–130357.","mla":"Muschalik, Maximilian, et al. “Shapiq: Shapley Interactions for Machine Learning.” Advances in Neural Information Processing Systems (NeurIPS), vol. 37, 2024, pp. 130324–130357.","short":"M. Muschalik, H. Baniecki, F. Fumagalli, P. Kolpaczki, B. Hammer, E. Huellermeier, in: Advances in Neural Information Processing Systems (NeurIPS), 2024, pp. 130324–130357.","bibtex":"@inproceedings{Muschalik_Baniecki_Fumagalli_Kolpaczki_Hammer_Huellermeier_2024, title={shapiq: Shapley interactions for machine learning}, volume={37}, booktitle={Advances in Neural Information Processing Systems (NeurIPS)}, author={Muschalik, Maximilian and Baniecki, Hubert and Fumagalli, Fabian and Kolpaczki, Patrick and Hammer, Barbara and Huellermeier, Eyke}, year={2024}, pages={130324–130357} }"},"page":"130324–130357","intvolume":" 37","year":"2024"},{"status":"public","publication":"26th International Conference on Discovery Science ","type":"conference","language":[{"iso":"eng"}],"_id":"51373","user_id":"54779","series_title":"Lecture Notes in Computer Science","place":"Cham","year":"2023","intvolume":" 14050","page":"189-203","citation":{"ama":"Hanselle JM, Fürnkranz J, Hüllermeier E. Probabilistic Scoring Lists for Interpretable Machine Learning. In: 26th International Conference on Discovery Science . Vol 14050. Lecture Notes in Computer Science. Springer Nature Switzerland; 2023:189-203. doi:10.1007/978-3-031-45275-8_13","chicago":"Hanselle, Jonas Manuel, Johannes Fürnkranz, and Eyke Hüllermeier. “Probabilistic Scoring Lists for Interpretable Machine Learning.” In 26th International Conference on Discovery Science , 14050:189–203. Lecture Notes in Computer Science. Cham: Springer Nature Switzerland, 2023. https://doi.org/10.1007/978-3-031-45275-8_13.","ieee":"J. M. Hanselle, J. Fürnkranz, and E. Hüllermeier, “Probabilistic Scoring Lists for Interpretable Machine Learning,” in 26th International Conference on Discovery Science , Porto, 2023, vol. 14050, pp. 189–203, doi: 10.1007/978-3-031-45275-8_13.","short":"J.M. Hanselle, J. Fürnkranz, E. Hüllermeier, in: 26th International Conference on Discovery Science , Springer Nature Switzerland, Cham, 2023, pp. 189–203.","bibtex":"@inproceedings{Hanselle_Fürnkranz_Hüllermeier_2023, place={Cham}, series={Lecture Notes in Computer Science}, title={Probabilistic Scoring Lists for Interpretable Machine Learning}, volume={14050}, DOI={10.1007/978-3-031-45275-8_13}, booktitle={26th International Conference on Discovery Science }, publisher={Springer Nature Switzerland}, author={Hanselle, Jonas Manuel and Fürnkranz, Johannes and Hüllermeier, Eyke}, year={2023}, pages={189–203}, collection={Lecture Notes in Computer Science} }","mla":"Hanselle, Jonas Manuel, et al. “Probabilistic Scoring Lists for Interpretable Machine Learning.” 26th International Conference on Discovery Science , vol. 14050, Springer Nature Switzerland, 2023, pp. 189–203, doi:10.1007/978-3-031-45275-8_13.","apa":"Hanselle, J. M., Fürnkranz, J., & Hüllermeier, E. (2023). 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Hanselle, E. Hüllermeier, F. Mohr, A.-C. Ngonga Ngomo, M. Sherif, A. Tornede, M.D. Wever, in: C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, H. Wehrheim (Eds.), On-The-Fly Computing – Individualized IT-Services in Dynamic Markets, Heinz Nixdorf Institut, Universität Paderborn, 2023, pp. 85–104.","apa":"Hanselle, J. M., Hüllermeier, E., Mohr, F., Ngonga Ngomo, A.-C., Sherif, M., Tornede, A., & Wever, M. D. (2023). Configuration and Evaluation. In C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, & H. Wehrheim (Eds.), On-The-Fly Computing – Individualized IT-services in dynamic markets (Vol. 412, pp. 85–104). Heinz Nixdorf Institut, Universität Paderborn. https://doi.org/10.5281/zenodo.8068466","chicago":"Hanselle, Jonas Manuel, Eyke Hüllermeier, Felix Mohr, Axel-Cyrille Ngonga Ngomo, Mohamed Sherif, Alexander Tornede, and Marcel Dominik Wever. “Configuration and Evaluation.” In On-The-Fly Computing – Individualized IT-Services in Dynamic Markets, edited by Claus-Jochen Haake, Friedhelm Meyer auf der Heide, Marco Platzner, Henning Wachsmuth, and Heike Wehrheim, 412:85–104. Verlagsschriftenreihe Des Heinz Nixdorf Instituts. Heinz Nixdorf Institut, Universität Paderborn, 2023. https://doi.org/10.5281/zenodo.8068466.","ieee":"J. M. Hanselle et al., “Configuration and Evaluation,” in On-The-Fly Computing – Individualized IT-services in dynamic markets, vol. 412, C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, and H. Wehrheim, Eds. Heinz Nixdorf Institut, Universität Paderborn, 2023, pp. 85–104.","ama":"Hanselle JM, Hüllermeier E, Mohr F, et al. Configuration and Evaluation. In: Haake C-J, Meyer auf der Heide F, Platzner M, Wachsmuth H, Wehrheim H, eds. On-The-Fly Computing – Individualized IT-Services in Dynamic Markets. Vol 412. Verlagsschriftenreihe des Heinz Nixdorf Instituts. Heinz Nixdorf Institut, Universität Paderborn; 2023:85–104. doi:10.5281/zenodo.8068466"},"intvolume":" 412","page":"85–104"},{"status":"public","type":"book_chapter","publication":"Discovery Science","language":[{"iso":"eng"}],"user_id":"72497","department":[{"_id":"660"}],"project":[{"name":"TRR 318 - C2: TRR 318 - Subproject C2","_id":"125"}],"_id":"54909","citation":{"mla":"Hanselle, Jonas Manuel, et al. “Probabilistic Scoring Lists for Interpretable Machine Learning.” Discovery Science, Springer Nature Switzerland, 2023, doi:10.1007/978-3-031-45275-8_13.","short":"J.M. Hanselle, J. Fürnkranz, E. Hüllermeier, in: Discovery Science, Springer Nature Switzerland, Cham, 2023.","bibtex":"@inbook{Hanselle_Fürnkranz_Hüllermeier_2023, place={Cham}, title={Probabilistic Scoring Lists for Interpretable Machine Learning}, DOI={10.1007/978-3-031-45275-8_13}, booktitle={Discovery Science}, publisher={Springer Nature Switzerland}, author={Hanselle, Jonas Manuel and Fürnkranz, Johannes and Hüllermeier, Eyke}, year={2023} }","apa":"Hanselle, J. M., Fürnkranz, J., & Hüllermeier, E. (2023). Probabilistic Scoring Lists for Interpretable Machine Learning. In Discovery Science. Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-45275-8_13","ama":"Hanselle JM, Fürnkranz J, Hüllermeier E. Probabilistic Scoring Lists for Interpretable Machine Learning. In: Discovery Science. Springer Nature Switzerland; 2023. doi:10.1007/978-3-031-45275-8_13","ieee":"J. M. Hanselle, J. Fürnkranz, and E. Hüllermeier, “Probabilistic Scoring Lists for Interpretable Machine Learning,” in Discovery Science, Cham: Springer Nature Switzerland, 2023.","chicago":"Hanselle, Jonas Manuel, Johannes Fürnkranz, and Eyke Hüllermeier. “Probabilistic Scoring Lists for Interpretable Machine Learning.” In Discovery Science. Cham: Springer Nature Switzerland, 2023. https://doi.org/10.1007/978-3-031-45275-8_13."},"year":"2023","place":"Cham","publication_status":"published","publication_identifier":{"issn":["0302-9743","1611-3349"],"isbn":["9783031452741","9783031452758"]},"doi":"10.1007/978-3-031-45275-8_13","title":"Probabilistic Scoring Lists for Interpretable Machine Learning","author":[{"first_name":"Jonas Manuel","last_name":"Hanselle","orcid":"0000-0002-1231-4985","id":"43980","full_name":"Hanselle, Jonas Manuel"},{"last_name":"Fürnkranz","full_name":"Fürnkranz, Johannes","first_name":"Johannes"},{"full_name":"Hüllermeier, Eyke","id":"48129","last_name":"Hüllermeier","first_name":"Eyke"}],"date_created":"2024-06-26T14:24:29Z","publisher":"Springer Nature Switzerland","date_updated":"2024-06-26T14:25:50Z"},{"year":"2023","citation":{"apa":"Uhlemeyer, S., Lienen, J., Hüllermeier, E., & Gottschalk, H. (2023). Detecting Novelties with Empty Classes. In arXiv:2305.00983.","mla":"Uhlemeyer, Svenja, et al. “Detecting Novelties with Empty Classes.” ArXiv:2305.00983, 2023.","short":"S. Uhlemeyer, J. Lienen, E. Hüllermeier, H. Gottschalk, ArXiv:2305.00983 (2023).","bibtex":"@article{Uhlemeyer_Lienen_Hüllermeier_Gottschalk_2023, title={Detecting Novelties with Empty Classes}, journal={arXiv:2305.00983}, author={Uhlemeyer, Svenja and Lienen, Julian and Hüllermeier, Eyke and Gottschalk, Hanno}, year={2023} }","chicago":"Uhlemeyer, Svenja, Julian Lienen, Eyke Hüllermeier, and Hanno Gottschalk. “Detecting Novelties with Empty Classes.” ArXiv:2305.00983, 2023.","ieee":"S. Uhlemeyer, J. Lienen, E. Hüllermeier, and H. Gottschalk, “Detecting Novelties with Empty Classes,” arXiv:2305.00983. 2023.","ama":"Uhlemeyer S, Lienen J, Hüllermeier E, Gottschalk H. Detecting Novelties with Empty Classes. arXiv:230500983. Published online 2023."},"title":"Detecting Novelties with Empty Classes","main_file_link":[{"url":"https://arxiv.org/pdf/2305.00983.pdf","open_access":"1"}],"date_updated":"2023-05-05T11:39:10Z","oa":"1","author":[{"last_name":"Uhlemeyer","full_name":"Uhlemeyer, Svenja","first_name":"Svenja"},{"last_name":"Lienen","id":"44040","full_name":"Lienen, Julian","first_name":"Julian"},{"last_name":"Hüllermeier","full_name":"Hüllermeier, Eyke","id":"48129","first_name":"Eyke"},{"last_name":"Gottschalk","full_name":"Gottschalk, Hanno","first_name":"Hanno"}],"date_created":"2023-05-05T11:37:00Z","abstract":[{"lang":"eng","text":"For open world applications, deep neural networks (DNNs) need to be aware of\r\npreviously unseen data and adaptable to evolving environments. Furthermore, it\r\nis desirable to detect and learn novel classes which are not included in the\r\nDNNs underlying set of semantic classes in an unsupervised fashion. The method\r\nproposed in this article builds upon anomaly detection to retrieve\r\nout-of-distribution (OoD) data as candidates for new classes. We thereafter\r\nextend the DNN by $k$ empty classes and fine-tune it on the OoD data samples.\r\nTo this end, we introduce two loss functions, which 1) entice the DNN to assign\r\nOoD samples to the empty classes and 2) to minimize the inner-class feature\r\ndistances between them. Thus, instead of ground truth which contains labels for\r\nthe different novel classes, the DNN obtains a single OoD label together with a\r\ndistance matrix, which is computed in advance. We perform several experiments\r\nfor image classification and semantic segmentation, which demonstrate that a\r\nDNN can extend its own semantic space by multiple classes without having access\r\nto ground truth."}],"status":"public","type":"preprint","publication":"arXiv:2305.00983","language":[{"iso":"eng"}],"_id":"44512","external_id":{"arxiv":["2305.00983"]},"user_id":"44040"},{"language":[{"iso":"eng"}],"user_id":"44040","_id":"31880","status":"public","abstract":[{"text":"The notion of neural collapse refers to several emergent phenomena that have been empirically observed across various canonical classification problems. During the terminal phase of training a deep neural network, the feature embedding of all examples of the same class tend to collapse to a single representation, and the features of different classes tend to separate as much as possible. Neural collapse is often studied through a simplified model, called the unconstrained feature representation, in which the model is assumed to have \"infinite expressivity\" and can map each data point to any arbitrary representation. In this work, we propose a more realistic variant of the unconstrained feature representation that takes the limited expressivity of the network into account. Empirical evidence suggests that the memorization of noisy data points leads to a degradation (dilation) of the neural collapse. Using a model of the memorization-dilation (M-D) phenomenon, we show one mechanism by which different losses lead to different performances of the trained network on noisy data. Our proofs reveal why label smoothing, a modification of cross-entropy empirically observed to produce a regularization effect, leads to improved generalization in classification tasks.","lang":"eng"}],"type":"conference","publication":"International Conference on Learning Representations, ICLR","main_file_link":[{"url":"https://arxiv.org/abs/2206.05530","open_access":"1"}],"conference":{"name":"International Conference on Learning Representations, ICLR","location":"Kigali, Ruanda"},"title":"Memorization-Dilation: Modeling Neural Collapse Under Noise","date_created":"2022-06-14T14:48:36Z","author":[{"full_name":"Nguyen, Duc Anh","last_name":"Nguyen","first_name":"Duc Anh"},{"first_name":"Ron","last_name":"Levie","full_name":"Levie, Ron"},{"id":"44040","full_name":"Lienen, Julian","last_name":"Lienen","first_name":"Julian"},{"first_name":"Gitta","last_name":"Kutyniok","full_name":"Kutyniok, Gitta"},{"first_name":"Eyke","full_name":"Hüllermeier, Eyke","id":"48129","last_name":"Hüllermeier"}],"oa":"1","date_updated":"2023-06-29T09:14:26Z","citation":{"chicago":"Nguyen, Duc Anh, Ron Levie, Julian Lienen, Gitta Kutyniok, and Eyke Hüllermeier. “Memorization-Dilation: Modeling Neural Collapse Under Noise.” In International Conference on Learning Representations, ICLR, 2023.","ieee":"D. A. Nguyen, R. Levie, J. Lienen, G. Kutyniok, and E. Hüllermeier, “Memorization-Dilation: Modeling Neural Collapse Under Noise,” presented at the International Conference on Learning Representations, ICLR, Kigali, Ruanda, 2023.","ama":"Nguyen DA, Levie R, Lienen J, Kutyniok G, Hüllermeier E. Memorization-Dilation: Modeling Neural Collapse Under Noise. In: International Conference on Learning Representations, ICLR. ; 2023.","apa":"Nguyen, D. A., Levie, R., Lienen, J., Kutyniok, G., & Hüllermeier, E. (2023). Memorization-Dilation: Modeling Neural Collapse Under Noise. International Conference on Learning Representations, ICLR. International Conference on Learning Representations, ICLR, Kigali, Ruanda.","mla":"Nguyen, Duc Anh, et al. “Memorization-Dilation: Modeling Neural Collapse Under Noise.” International Conference on Learning Representations, ICLR, 2023.","short":"D.A. Nguyen, R. Levie, J. Lienen, G. Kutyniok, E. Hüllermeier, in: International Conference on Learning Representations, ICLR, 2023.","bibtex":"@inproceedings{Nguyen_Levie_Lienen_Kutyniok_Hüllermeier_2023, title={Memorization-Dilation: Modeling Neural Collapse Under Noise}, booktitle={International Conference on Learning Representations, ICLR}, author={Nguyen, Duc Anh and Levie, Ron and Lienen, Julian and Kutyniok, Gitta and Hüllermeier, Eyke}, year={2023} }"},"year":"2023"},{"ddc":["040"],"language":[{"iso":"eng"}],"publication":"On-The-Fly Computing -- Individualized IT-services in dynamic markets","file":[{"creator":"florida","date_created":"2023-07-07T07:50:34Z","date_updated":"2023-07-07T11:20:11Z","access_level":"open_access","file_name":"B2-Chapter-SFB-Buch-Final.pdf","file_id":"45885","file_size":895091,"content_type":"application/pdf","relation":"main_file"}],"publisher":"Heinz Nixdorf Institut, Universität Paderborn","date_created":"2023-07-07T07:50:53Z","title":"Configuration and Evaluation","year":"2023","project":[{"grant_number":"160364472","name":"SFB 901: SFB 901: On-The-Fly Computing - Individualisierte IT-Dienstleistungen in dynamischen Märkten ","_id":"1"},{"_id":"3","name":"SFB 901 - B: SFB 901 - Project Area B"},{"grant_number":"160364472","name":"SFB 901 - B2: Konfiguration und Bewertung (B02)","_id":"10"}],"_id":"45884","user_id":"477","series_title":"Verlagsschriftenreihe des Heinz Nixdorf Instituts","department":[{"_id":"7"}],"file_date_updated":"2023-07-07T11:20:11Z","type":"book_chapter","editor":[{"full_name":"Haake, Claus-Jochen","last_name":"Haake","first_name":"Claus-Jochen"},{"first_name":"Friedhelm","last_name":"Meyer auf der Heide","full_name":"Meyer auf der Heide, Friedhelm"},{"first_name":"Marco","last_name":"Platzner","full_name":"Platzner, Marco"},{"last_name":"Wachsmuth","full_name":"Wachsmuth, Henning","first_name":"Henning"},{"first_name":"Heike","last_name":"Wehrheim","full_name":"Wehrheim, Heike"}],"status":"public","oa":"1","date_updated":"2023-07-07T11:20:12Z","author":[{"first_name":"Jonas Manuel","last_name":"Hanselle","orcid":"0000-0002-1231-4985","id":"43980","full_name":"Hanselle, Jonas Manuel"},{"last_name":"Hüllermeier","full_name":"Hüllermeier, Eyke","id":"48129","first_name":"Eyke"},{"full_name":"Mohr, Felix","last_name":"Mohr","first_name":"Felix"},{"last_name":"Ngonga Ngomo","full_name":"Ngonga Ngomo, Axel-Cyrille","id":"65716","first_name":"Axel-Cyrille"},{"full_name":"Sherif, Mohamed","id":"67234","orcid":"https://orcid.org/0000-0002-9927-2203","last_name":"Sherif","first_name":"Mohamed"},{"last_name":"Tornede","full_name":"Tornede, Alexander","id":"38209","first_name":"Alexander"},{"orcid":" https://orcid.org/0000-0001-9782-6818","last_name":"Wever","id":"33176","full_name":"Wever, Marcel Dominik","first_name":"Marcel Dominik"}],"volume":412,"doi":"10.5281/zenodo.8068466","has_accepted_license":"1","place":"Paderborn","citation":{"bibtex":"@inbook{Hanselle_Hüllermeier_Mohr_Ngonga Ngomo_Sherif_Tornede_Wever_2023, place={Paderborn}, series={Verlagsschriftenreihe des Heinz Nixdorf Instituts}, title={Configuration and Evaluation}, volume={412}, DOI={10.5281/zenodo.8068466}, booktitle={On-The-Fly Computing -- Individualized IT-services in dynamic markets}, publisher={Heinz Nixdorf Institut, Universität Paderborn}, author={Hanselle, Jonas Manuel and Hüllermeier, Eyke and Mohr, Felix and Ngonga Ngomo, Axel-Cyrille and Sherif, Mohamed and Tornede, Alexander and Wever, Marcel Dominik}, editor={Haake, Claus-Jochen and Meyer auf der Heide, Friedhelm and Platzner, Marco and Wachsmuth, Henning and Wehrheim, Heike}, year={2023}, pages={85–104}, collection={Verlagsschriftenreihe des Heinz Nixdorf Instituts} }","short":"J.M. Hanselle, E. Hüllermeier, F. Mohr, A.-C. Ngonga Ngomo, M. Sherif, A. Tornede, M.D. Wever, in: C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, H. Wehrheim (Eds.), On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets, Heinz Nixdorf Institut, Universität Paderborn, Paderborn, 2023, pp. 85–104.","mla":"Hanselle, Jonas Manuel, et al. “Configuration and Evaluation.” On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets, edited by Claus-Jochen Haake et al., vol. 412, Heinz Nixdorf Institut, Universität Paderborn, 2023, pp. 85–104, doi:10.5281/zenodo.8068466.","apa":"Hanselle, J. M., Hüllermeier, E., Mohr, F., Ngonga Ngomo, A.-C., Sherif, M., Tornede, A., & Wever, M. D. (2023). Configuration and Evaluation. In C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, & H. Wehrheim (Eds.), On-The-Fly Computing -- Individualized IT-services in dynamic markets (Vol. 412, pp. 85–104). Heinz Nixdorf Institut, Universität Paderborn. https://doi.org/10.5281/zenodo.8068466","ieee":"J. M. Hanselle et al., “Configuration and Evaluation,” in On-The-Fly Computing -- Individualized IT-services in dynamic markets, vol. 412, C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, and H. Wehrheim, Eds. Paderborn: Heinz Nixdorf Institut, Universität Paderborn, 2023, pp. 85–104.","chicago":"Hanselle, Jonas Manuel, Eyke Hüllermeier, Felix Mohr, Axel-Cyrille Ngonga Ngomo, Mohamed Sherif, Alexander Tornede, and Marcel Dominik Wever. “Configuration and Evaluation.” In On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets, edited by Claus-Jochen Haake, Friedhelm Meyer auf der Heide, Marco Platzner, Henning Wachsmuth, and Heike Wehrheim, 412:85–104. Verlagsschriftenreihe Des Heinz Nixdorf Instituts. Paderborn: Heinz Nixdorf Institut, Universität Paderborn, 2023. https://doi.org/10.5281/zenodo.8068466.","ama":"Hanselle JM, Hüllermeier E, Mohr F, et al. Configuration and Evaluation. In: Haake C-J, Meyer auf der Heide F, Platzner M, Wachsmuth H, Wehrheim H, eds. On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets. Vol 412. Verlagsschriftenreihe des Heinz Nixdorf Instituts. Heinz Nixdorf Institut, Universität Paderborn; 2023:85-104. doi:10.5281/zenodo.8068466"},"page":"85-104","intvolume":" 412"},{"date_created":"2023-07-07T07:56:08Z","publisher":"Heinz Nixdorf Institut, Universität Paderborn","title":"Composition Analysis in Unknown Contexts","year":"2023","language":[{"iso":"eng"}],"ddc":["004"],"publication":"On-The-Fly Computing -- Individualized IT-services in dynamic markets","file":[{"file_id":"45887","access_level":"open_access","file_name":"B3-Chapter-SFB-Buch-Final.pdf","file_size":370888,"date_created":"2023-07-07T07:55:57Z","creator":"florida","date_updated":"2023-07-07T11:19:40Z","relation":"main_file","content_type":"application/pdf"}],"volume":412,"author":[{"full_name":"Wehrheim, Heike","id":"573","last_name":"Wehrheim","first_name":"Heike"},{"full_name":"Hüllermeier, Eyke","id":"48129","last_name":"Hüllermeier","first_name":"Eyke"},{"first_name":"Steffen","full_name":"Becker, Steffen","last_name":"Becker"},{"full_name":"Becker, Matthias","last_name":"Becker","first_name":"Matthias"},{"last_name":"Richter","full_name":"Richter, Cedric","id":"50003","first_name":"Cedric"},{"id":"67200","full_name":"Sharma, Arnab","last_name":"Sharma","first_name":"Arnab"}],"date_updated":"2023-07-07T11:19:40Z","oa":"1","doi":"10.5281/zenodo.8068510","has_accepted_license":"1","intvolume":" 412","page":"105-123","citation":{"ama":"Wehrheim H, Hüllermeier E, Becker S, Becker M, Richter C, Sharma A. Composition Analysis in Unknown Contexts. In: Haake C-J, Meyer auf der Heide F, Platzner M, Wachsmuth H, Wehrheim H, eds. On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets. Vol 412. Verlagsschriftenreihe des Heinz Nixdorf Instituts. Heinz Nixdorf Institut, Universität Paderborn; 2023:105-123. doi:10.5281/zenodo.8068510","chicago":"Wehrheim, Heike, Eyke Hüllermeier, Steffen Becker, Matthias Becker, Cedric Richter, and Arnab Sharma. “Composition Analysis in Unknown Contexts.” In On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets, edited by Claus-Jochen Haake, Friedhelm Meyer auf der Heide, Marco Platzner, Henning Wachsmuth, and Heike Wehrheim, 412:105–23. Verlagsschriftenreihe Des Heinz Nixdorf Instituts. Paderborn: Heinz Nixdorf Institut, Universität Paderborn, 2023. https://doi.org/10.5281/zenodo.8068510.","ieee":"H. Wehrheim, E. Hüllermeier, S. Becker, M. Becker, C. Richter, and A. Sharma, “Composition Analysis in Unknown Contexts,” in On-The-Fly Computing -- Individualized IT-services in dynamic markets, vol. 412, C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, and H. Wehrheim, Eds. Paderborn: Heinz Nixdorf Institut, Universität Paderborn, 2023, pp. 105–123.","bibtex":"@inbook{Wehrheim_Hüllermeier_Becker_Becker_Richter_Sharma_2023, place={Paderborn}, series={Verlagsschriftenreihe des Heinz Nixdorf Instituts}, title={Composition Analysis in Unknown Contexts}, volume={412}, DOI={10.5281/zenodo.8068510}, booktitle={On-The-Fly Computing -- Individualized IT-services in dynamic markets}, publisher={Heinz Nixdorf Institut, Universität Paderborn}, author={Wehrheim, Heike and Hüllermeier, Eyke and Becker, Steffen and Becker, Matthias and Richter, Cedric and Sharma, Arnab}, editor={Haake, Claus-Jochen and Meyer auf der Heide, Friedhelm and Platzner, Marco and Wachsmuth, Henning and Wehrheim, Heike}, year={2023}, pages={105–123}, collection={Verlagsschriftenreihe des Heinz Nixdorf Instituts} }","mla":"Wehrheim, Heike, et al. “Composition Analysis in Unknown Contexts.” On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets, edited by Claus-Jochen Haake et al., vol. 412, Heinz Nixdorf Institut, Universität Paderborn, 2023, pp. 105–23, doi:10.5281/zenodo.8068510.","short":"H. Wehrheim, E. Hüllermeier, S. Becker, M. Becker, C. Richter, A. Sharma, in: C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, H. Wehrheim (Eds.), On-The-Fly Computing -- Individualized IT-Services in Dynamic Markets, Heinz Nixdorf Institut, Universität Paderborn, Paderborn, 2023, pp. 105–123.","apa":"Wehrheim, H., Hüllermeier, E., Becker, S., Becker, M., Richter, C., & Sharma, A. (2023). Composition Analysis in Unknown Contexts. In C.-J. Haake, F. Meyer auf der Heide, M. Platzner, H. Wachsmuth, & H. Wehrheim (Eds.), On-The-Fly Computing -- Individualized IT-services in dynamic markets (Vol. 412, pp. 105–123). Heinz Nixdorf Institut, Universität Paderborn. https://doi.org/10.5281/zenodo.8068510"},"place":"Paderborn","department":[{"_id":"7"}],"user_id":"477","series_title":"Verlagsschriftenreihe des Heinz Nixdorf Instituts","_id":"45886","project":[{"name":"SFB 901: SFB 901: On-The-Fly Computing - Individualisierte IT-Dienstleistungen in dynamischen Märkten ","_id":"1","grant_number":"160364472"},{"name":"SFB 901 - B: SFB 901 - Project Area B","_id":"3"},{"_id":"11","name":"SFB 901 - B3: SFB 901 - Subproject B3"}],"file_date_updated":"2023-07-07T11:19:40Z","type":"book_chapter","status":"public","editor":[{"last_name":"Haake","full_name":"Haake, Claus-Jochen","first_name":"Claus-Jochen"},{"first_name":"Friedhelm","full_name":"Meyer auf der Heide, Friedhelm","last_name":"Meyer auf der Heide"},{"last_name":"Platzner","full_name":"Platzner, Marco","first_name":"Marco"},{"full_name":"Wachsmuth, Henning","last_name":"Wachsmuth","first_name":"Henning"},{"first_name":"Heike","last_name":"Wehrheim","full_name":"Wehrheim, Heike"}]},{"citation":{"apa":"Lienen, J., & Hüllermeier, E. (2023). Mitigating Label Noise through Data Ambiguation. In arXiv:2305.13764.","short":"J. Lienen, E. Hüllermeier, ArXiv:2305.13764 (2023).","mla":"Lienen, Julian, and Eyke Hüllermeier. “Mitigating Label Noise through Data Ambiguation.” ArXiv:2305.13764, 2023.","bibtex":"@article{Lienen_Hüllermeier_2023, title={Mitigating Label Noise through Data Ambiguation}, journal={arXiv:2305.13764}, author={Lienen, Julian and Hüllermeier, Eyke}, year={2023} }","ama":"Lienen J, Hüllermeier E. Mitigating Label Noise through Data Ambiguation. arXiv:230513764. Published online 2023.","ieee":"J. Lienen and E. Hüllermeier, “Mitigating Label Noise through Data Ambiguation,” arXiv:2305.13764. 2023.","chicago":"Lienen, Julian, and Eyke Hüllermeier. “Mitigating Label Noise through Data Ambiguation.” ArXiv:2305.13764, 2023."},"year":"2023","main_file_link":[{"url":"https://arxiv.org/abs/2305.13764","open_access":"1"}],"title":"Mitigating Label Noise through Data Ambiguation","author":[{"first_name":"Julian","full_name":"Lienen, Julian","id":"44040","last_name":"Lienen"},{"first_name":"Eyke","last_name":"Hüllermeier","full_name":"Hüllermeier, Eyke","id":"48129"}],"date_created":"2023-07-09T11:25:48Z","oa":"1","date_updated":"2023-07-09T11:26:21Z","status":"public","abstract":[{"text":"Label noise poses an important challenge in machine learning, especially in\r\ndeep learning, in which large models with high expressive power dominate the\r\nfield. Models of that kind are prone to memorizing incorrect labels, thereby\r\nharming generalization performance. Many methods have been proposed to address\r\nthis problem, including robust loss functions and more complex label correction\r\napproaches. Robust loss functions are appealing due to their simplicity, but\r\ntypically lack flexibility, while label correction usually adds substantial\r\ncomplexity to the training setup. In this paper, we suggest to address the\r\nshortcomings of both methodologies by \"ambiguating\" the target information,\r\nadding additional, complementary candidate labels in case the learner is not\r\nsufficiently convinced of the observed training label. More precisely, we\r\nleverage the framework of so-called superset learning to construct set-valued\r\ntargets based on a confidence threshold, which deliver imprecise yet more\r\nreliable beliefs about the ground-truth, effectively helping the learner to\r\nsuppress the memorization effect. In an extensive empirical evaluation, our\r\nmethod demonstrates favorable learning behavior on synthetic and real-world\r\nnoise, confirming the effectiveness in detecting and correcting erroneous\r\ntraining labels.","lang":"eng"}],"publication":"arXiv:2305.13764","type":"preprint","language":[{"iso":"eng"}],"user_id":"44040","external_id":{"arxiv":["2305.13764"]},"_id":"45911"}]