--- _id: '48847' abstract: - lang: eng text: Dynamic optimization problems have gained significant attention in evolutionary computation as evolutionary algorithms (EAs) can easily adapt to changing environments. We show that EAs can solve the graph coloring problem for bipartite graphs more efficiently by using dynamic optimization. In our approach the graph instance is given incrementally such that the EA can reoptimize its coloring when a new edge introduces a conflict. We show that, when edges are inserted in a way that preserves graph connectivity, Randomized Local Search (RLS) efficiently finds a proper 2-coloring for all bipartite graphs. This includes graphs for which RLS and other EAs need exponential expected time in a static optimization scenario. We investigate different ways of building up the graph by popular graph traversals such as breadth-first-search and depth-first-search and analyse the resulting runtime behavior. We further show that offspring populations (e. g. a (1 + {$\lambda$}) RLS) lead to an exponential speedup in {$\lambda$}. Finally, an island model using 3 islands succeeds in an optimal time of {$\Theta$}(m) on every m-edge bipartite graph, outperforming offspring populations. This is the first example where an island model guarantees a speedup that is not bounded in the number of islands. author: - first_name: Jakob full_name: Bossek, Jakob id: '102979' last_name: Bossek orcid: 0000-0002-4121-4668 - first_name: Frank full_name: Neumann, Frank last_name: Neumann - first_name: Pan full_name: Peng, Pan last_name: Peng - first_name: Dirk full_name: Sudholt, Dirk last_name: Sudholt citation: ama: 'Bossek J, Neumann F, Peng P, Sudholt D. More Effective Randomized Search Heuristics for Graph Coloring through Dynamic Optimization. In: Proceedings of the Genetic and Evolutionary Computation Conference. GECCO ’20. Association for Computing Machinery; 2020:1277–1285. doi:10.1145/3377930.3390174' apa: Bossek, J., Neumann, F., Peng, P., & Sudholt, D. (2020). More Effective Randomized Search Heuristics for Graph Coloring through Dynamic Optimization. Proceedings of the Genetic and Evolutionary Computation Conference, 1277–1285. https://doi.org/10.1145/3377930.3390174 bibtex: '@inproceedings{Bossek_Neumann_Peng_Sudholt_2020, place={New York, NY, USA}, series={GECCO ’20}, title={More Effective Randomized Search Heuristics for Graph Coloring through Dynamic Optimization}, DOI={10.1145/3377930.3390174}, booktitle={Proceedings of the Genetic and Evolutionary Computation Conference}, publisher={Association for Computing Machinery}, author={Bossek, Jakob and Neumann, Frank and Peng, Pan and Sudholt, Dirk}, year={2020}, pages={1277–1285}, collection={GECCO ’20} }' chicago: 'Bossek, Jakob, Frank Neumann, Pan Peng, and Dirk Sudholt. “More Effective Randomized Search Heuristics for Graph Coloring through Dynamic Optimization.” In Proceedings of the Genetic and Evolutionary Computation Conference, 1277–1285. GECCO ’20. New York, NY, USA: Association for Computing Machinery, 2020. https://doi.org/10.1145/3377930.3390174.' ieee: 'J. Bossek, F. Neumann, P. Peng, and D. Sudholt, “More Effective Randomized Search Heuristics for Graph Coloring through Dynamic Optimization,” in Proceedings of the Genetic and Evolutionary Computation Conference, 2020, pp. 1277–1285, doi: 10.1145/3377930.3390174.' mla: Bossek, Jakob, et al. “More Effective Randomized Search Heuristics for Graph Coloring through Dynamic Optimization.” Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, 2020, pp. 1277–1285, doi:10.1145/3377930.3390174. short: 'J. Bossek, F. Neumann, P. Peng, D. Sudholt, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2020, pp. 1277–1285.' date_created: 2023-11-14T15:58:53Z date_updated: 2023-12-13T10:43:41Z department: - _id: '819' doi: 10.1145/3377930.3390174 extern: '1' keyword: - dynamic optimization - evolutionary algorithms - running time analysis - theory language: - iso: eng page: 1277–1285 place: New York, NY, USA publication: Proceedings of the Genetic and Evolutionary Computation Conference publication_identifier: isbn: - 978-1-4503-7128-5 publication_status: published publisher: Association for Computing Machinery series_title: GECCO ’20 status: public title: More Effective Randomized Search Heuristics for Graph Coloring through Dynamic Optimization type: conference user_id: '102979' year: '2020' ... --- _id: '24250' author: - first_name: Elmar full_name: Moritzer, Elmar id: '20531' last_name: Moritzer - first_name: Frederik Marvin full_name: Mühlhoff, Frederik Marvin id: '41312' last_name: Mühlhoff - first_name: Erhard full_name: Krampe, Erhard last_name: Krampe - first_name: Birte full_name: Böhnke, Birte last_name: Böhnke citation: ama: Moritzer E, Mühlhoff FM, Krampe E, Böhnke B. More Material Combinations, Lower Costs. Kunststoffe international. Published online 2020:22-25. apa: Moritzer, E., Mühlhoff, F. M., Krampe, E., & Böhnke, B. (2020). More Material Combinations, Lower Costs. Kunststoffe International, 22–25. bibtex: '@article{Moritzer_Mühlhoff_Krampe_Böhnke_2020, title={More Material Combinations, Lower Costs}, journal={Kunststoffe international}, author={Moritzer, Elmar and Mühlhoff, Frederik Marvin and Krampe, Erhard and Böhnke, Birte}, year={2020}, pages={22–25} }' chicago: Moritzer, Elmar, Frederik Marvin Mühlhoff, Erhard Krampe, and Birte Böhnke. “More Material Combinations, Lower Costs.” Kunststoffe International, 2020, 22–25. ieee: E. Moritzer, F. M. Mühlhoff, E. Krampe, and B. Böhnke, “More Material Combinations, Lower Costs,” Kunststoffe international, pp. 22–25, 2020. mla: Moritzer, Elmar, et al. “More Material Combinations, Lower Costs.” Kunststoffe International, 2020, pp. 22–25. short: E. Moritzer, F.M. Mühlhoff, E. Krampe, B. Böhnke, Kunststoffe International (2020) 22–25. date_created: 2021-09-13T09:09:36Z date_updated: 2022-01-06T06:56:13Z department: - _id: '9' - _id: '367' - _id: '321' language: - iso: eng page: 22-25 publication: Kunststoffe international status: public title: More Material Combinations, Lower Costs type: journal_article user_id: '44116' year: '2020' ... --- _id: '35701' author: - first_name: Steffen full_name: Lünne, Steffen last_name: Lünne - first_name: Susanne full_name: Schnell, Susanne last_name: Schnell - first_name: Rolf full_name: Biehler, Rolf id: '16274' last_name: Biehler citation: ama: Lünne S, Schnell S, Biehler R. Motivation of out-of-field teachers for participating in professional development courses in mathematics. European Journal of Teacher Education. 2020;44(5):688-705. doi:10.1080/02619768.2020.1793950 apa: Lünne, S., Schnell, S., & Biehler, R. (2020). Motivation of out-of-field teachers for participating in professional development courses in mathematics. European Journal of Teacher Education, 44(5), 688–705. https://doi.org/10.1080/02619768.2020.1793950 bibtex: '@article{Lünne_Schnell_Biehler_2020, title={Motivation of out-of-field teachers for participating in professional development courses in mathematics}, volume={44}, DOI={10.1080/02619768.2020.1793950}, number={5}, journal={European Journal of Teacher Education}, publisher={Informa UK Limited}, author={Lünne, Steffen and Schnell, Susanne and Biehler, Rolf}, year={2020}, pages={688–705} }' chicago: 'Lünne, Steffen, Susanne Schnell, and Rolf Biehler. “Motivation of Out-of-Field Teachers for Participating in Professional Development Courses in Mathematics.” European Journal of Teacher Education 44, no. 5 (2020): 688–705. https://doi.org/10.1080/02619768.2020.1793950.' ieee: 'S. Lünne, S. Schnell, and R. Biehler, “Motivation of out-of-field teachers for participating in professional development courses in mathematics,” European Journal of Teacher Education, vol. 44, no. 5, pp. 688–705, 2020, doi: 10.1080/02619768.2020.1793950.' mla: Lünne, Steffen, et al. “Motivation of Out-of-Field Teachers for Participating in Professional Development Courses in Mathematics.” European Journal of Teacher Education, vol. 44, no. 5, Informa UK Limited, 2020, pp. 688–705, doi:10.1080/02619768.2020.1793950. short: S. Lünne, S. Schnell, R. Biehler, European Journal of Teacher Education 44 (2020) 688–705. date_created: 2023-01-10T09:08:17Z date_updated: 2023-01-11T10:18:30Z department: - _id: '34' - _id: '10' - _id: '97' - _id: '363' doi: 10.1080/02619768.2020.1793950 intvolume: ' 44' issue: '5' keyword: - Education language: - iso: eng page: 688-705 publication: European Journal of Teacher Education publication_identifier: issn: - 0261-9768 - 1469-5928 publication_status: published publisher: Informa UK Limited status: public title: Motivation of out-of-field teachers for participating in professional development courses in mathematics type: journal_article user_id: '37888' volume: 44 year: '2020' ... --- _id: '35298' abstract: - lang: ger text: Im Artikel werden drei verschiedene Lernzugänge (kom-petenzorientiertes, ästhetisches und biographisches Lernen) vorgestellt und aus theoretischer Perspektive deren motivierender Gehalt für selbstreguliertes Lernen in Praxisphasen des Lehramtsstudiumsherausgearbeitet. Als theoretische Grund-lage dient die Selbstbestimmungstheorie als zentrale motivationale Theorie zur Erklärung selbstbestimmten Handelns. - lang: eng text: The article addresses how motivational learning approaches (competency-oriented, aesthetic and biographical) can contribute to the professionalization of preservice teachers during a long-term internship. As a theoretical basis, the self-determination theory serves as a central motivational theory for explaining self-determined action. alternative_title: - Ein Blick auf kompetenzorientiertes, ästhetisches und biographisches Lernen im Lehramtsstudium author: - first_name: Carina full_name: Caruso, Carina id: '23123' last_name: Caruso - first_name: Christine full_name: Adammek, Christine last_name: Adammek - first_name: Sabrina full_name: Bonanati, Sabrina last_name: Bonanati - first_name: Sybille full_name: Wiescholek, Sybille last_name: Wiescholek citation: ama: Caruso C, Adammek C, Bonanati S, Wiescholek S. Motivierende Lernzugänge als Ausgangspunkt der Professionalisierung angehender Lehrer_innen. Herausforderung Lehrer*innenbildung - Zeitschrift Zur Konzeption, Gestaltung Und Diskussion. 2020;3(1):18-33. doi:10.4119/hlz-2540 apa: Caruso, C., Adammek, C., Bonanati, S., & Wiescholek, S. (2020). Motivierende Lernzugänge als Ausgangspunkt der Professionalisierung angehender Lehrer_innen. Herausforderung Lehrer*innenbildung - Zeitschrift Zur Konzeption, Gestaltung Und Diskussion, 3(1), 18–33. https://doi.org/10.4119/hlz-2540 bibtex: '@article{Caruso_Adammek_Bonanati_Wiescholek_2020, title={Motivierende Lernzugänge als Ausgangspunkt der Professionalisierung angehender Lehrer_innen}, volume={3}, DOI={10.4119/hlz-2540}, number={1}, journal={Herausforderung Lehrer*innenbildung - Zeitschrift Zur Konzeption, Gestaltung Und Diskussion}, author={Caruso, Carina and Adammek, Christine and Bonanati, Sabrina and Wiescholek, Sybille}, year={2020}, pages={18–33} }' chicago: 'Caruso, Carina, Christine Adammek, Sabrina Bonanati, and Sybille Wiescholek. “Motivierende Lernzugänge als Ausgangspunkt der Professionalisierung angehender Lehrer_innen.” Herausforderung Lehrer*innenbildung - Zeitschrift Zur Konzeption, Gestaltung Und Diskussion 3, no. 1 (2020): 18–33. https://doi.org/10.4119/hlz-2540.' ieee: 'C. Caruso, C. Adammek, S. Bonanati, and S. Wiescholek, “Motivierende Lernzugänge als Ausgangspunkt der Professionalisierung angehender Lehrer_innen,” Herausforderung Lehrer*innenbildung - Zeitschrift Zur Konzeption, Gestaltung Und Diskussion, vol. 3, no. 1, pp. 18–33, 2020, doi: 10.4119/hlz-2540.' mla: Caruso, Carina, et al. “Motivierende Lernzugänge als Ausgangspunkt der Professionalisierung angehender Lehrer_innen.” Herausforderung Lehrer*innenbildung - Zeitschrift Zur Konzeption, Gestaltung Und Diskussion, vol. 3, no. 1, 2020, pp. 18–33, doi:10.4119/hlz-2540. short: C. Caruso, C. Adammek, S. Bonanati, S. Wiescholek, Herausforderung Lehrer*innenbildung - Zeitschrift Zur Konzeption, Gestaltung Und Diskussion 3 (2020) 18–33. date_created: 2023-01-05T13:58:28Z date_updated: 2023-01-06T12:18:16Z doi: 10.4119/hlz-2540 intvolume: ' 3' issue: '1' keyword: - ästhetische Forschung - Biographiearbeit - Praxissemester - Professionalisierung - selbstreguliertes Lernen - Motivation / aesthetic research - biographical work - long-term internship - profes-sionalization - self-regulated learning - motivation language: - iso: other page: 18-33 publication: Herausforderung Lehrer*innenbildung - Zeitschrift Zur Konzeption, Gestaltung Und Diskussion publication_identifier: issn: - 2625-0675 publication_status: published status: public title: Motivierende Lernzugänge als Ausgangspunkt der Professionalisierung angehender Lehrer_innen type: journal_article user_id: '86519' volume: 3 year: '2020' ... --- _id: '21536' abstract: - lang: eng text: "We consider a resource-aware variant of the classical multi-armed bandit\r\nproblem: In each round, the learner selects an arm and determines a resource\r\nlimit. It then observes a corresponding (random) reward, provided the (random)\r\namount of consumed resources remains below the limit. Otherwise, the\r\nobservation is censored, i.e., no reward is obtained. For this problem setting,\r\nwe introduce a measure of regret, which incorporates the actual amount of\r\nallocated resources of each learning round as well as the optimality of\r\nrealizable rewards. Thus, to minimize regret, the learner needs to set a\r\nresource limit and choose an arm in such a way that the chance to realize a\r\nhigh reward within the predefined resource limit is high, while the resource\r\nlimit itself should be kept as low as possible. We derive the theoretical lower\r\nbound on the cumulative regret and propose a learning algorithm having a regret\r\nupper bound that matches the lower bound. In a simulation study, we show that\r\nour learning algorithm outperforms straightforward extensions of standard\r\nmulti-armed bandit algorithms." author: - first_name: Viktor full_name: Bengs, Viktor last_name: Bengs - first_name: Eyke full_name: Hüllermeier, Eyke last_name: Hüllermeier citation: ama: Bengs V, Hüllermeier E. Multi-Armed Bandits with Censored Consumption of Resources. arXiv:201100813. 2020. apa: Bengs, V., & Hüllermeier, E. (2020). Multi-Armed Bandits with Censored Consumption of Resources. ArXiv:2011.00813. bibtex: '@article{Bengs_Hüllermeier_2020, title={Multi-Armed Bandits with Censored Consumption of Resources}, journal={arXiv:2011.00813}, author={Bengs, Viktor and Hüllermeier, Eyke}, year={2020} }' chicago: Bengs, Viktor, and Eyke Hüllermeier. “Multi-Armed Bandits with Censored Consumption of Resources.” ArXiv:2011.00813, 2020. ieee: V. Bengs and E. Hüllermeier, “Multi-Armed Bandits with Censored Consumption of Resources,” arXiv:2011.00813. 2020. mla: Bengs, Viktor, and Eyke Hüllermeier. “Multi-Armed Bandits with Censored Consumption of Resources.” ArXiv:2011.00813, 2020. short: V. Bengs, E. Hüllermeier, ArXiv:2011.00813 (2020). date_created: 2021-03-18T11:27:37Z date_updated: 2022-01-06T06:55:03Z department: - _id: '34' - _id: '7' - _id: '355' language: - iso: eng project: - _id: '52' name: Computing Resources Provided by the Paderborn Center for Parallel Computing publication: arXiv:2011.00813 status: public title: Multi-Armed Bandits with Censored Consumption of Resources type: preprint user_id: '76599' year: '2020' ... --- _id: '32242' abstract: - lang: eng text: "We consider a resource-aware variant of the classical multi-armed bandit\r\nproblem: In each round, the learner selects an arm and determines a resource\r\nlimit. It then observes a corresponding (random) reward, provided the (random)\r\namount of consumed resources remains below the limit. Otherwise, the\r\nobservation is censored, i.e., no reward is obtained. For this problem setting,\r\nwe introduce a measure of regret, which incorporates the actual amount of\r\nallocated resources of each learning round as well as the optimality of\r\nrealizable rewards. Thus, to minimize regret, the learner needs to set a\r\nresource limit and choose an arm in such a way that the chance to realize a\r\nhigh reward within the predefined resource limit is high, while the resource\r\nlimit itself should be kept as low as possible. We derive the theoretical lower\r\nbound on the cumulative regret and propose a learning algorithm having a regret\r\nupper bound that matches the lower bound. In a simulation study, we show that\r\nour learning algorithm outperforms straightforward extensions of standard\r\nmulti-armed bandit algorithms." author: - first_name: Viktor full_name: Bengs, Viktor last_name: Bengs - first_name: Eyke full_name: Hüllermeier, Eyke last_name: Hüllermeier citation: ama: Bengs V, Hüllermeier E. Multi-Armed Bandits with Censored Consumption of Resources. arXiv:201100813. Published online 2020. apa: Bengs, V., & Hüllermeier, E. (2020). Multi-Armed Bandits with Censored Consumption of Resources. In arXiv:2011.00813. bibtex: '@article{Bengs_Hüllermeier_2020, title={Multi-Armed Bandits with Censored Consumption of Resources}, journal={arXiv:2011.00813}, author={Bengs, Viktor and Hüllermeier, Eyke}, year={2020} }' chicago: Bengs, Viktor, and Eyke Hüllermeier. “Multi-Armed Bandits with Censored Consumption of Resources.” ArXiv:2011.00813, 2020. ieee: V. Bengs and E. Hüllermeier, “Multi-Armed Bandits with Censored Consumption of Resources,” arXiv:2011.00813. 2020. mla: Bengs, Viktor, and Eyke Hüllermeier. “Multi-Armed Bandits with Censored Consumption of Resources.” ArXiv:2011.00813, 2020. short: V. Bengs, E. Hüllermeier, ArXiv:2011.00813 (2020). date_created: 2022-06-28T07:26:54Z date_updated: 2022-06-28T07:27:19Z department: - _id: '27' external_id: arxiv: - '2011.00813' language: - iso: eng project: - _id: '52' name: 'PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing' publication: arXiv:2011.00813 status: public title: Multi-Armed Bandits with Censored Consumption of Resources type: preprint user_id: '15278' year: '2020' ... --- _id: '16280' abstract: - lang: eng text: 'Assigning bands of the wireless spectrum as resources to users is a common problem in wireless networks. Typically, frequency bands were assumed to be available in a stable manner. Nevertheless, in recent scenarios where wireless networks may be deployed in unknown environments, spectrum competition is considered, making it uncertain whether a frequency band is available at all or at what quality. To fully exploit such resources with uncertain availability, the multi-armed bandit (MAB) method, a representative online learning technique, has been applied to design spectrum scheduling algorithms. This article surveys such proposals. We describe the following three aspects: how to model spectrum scheduling problems within the MAB framework, what the main thread is following which prevalent algorithms are designed, and how to evaluate algorithm performance and complexity. We also give some promising directions for future research in related fields.' author: - first_name: Feng full_name: Li, Feng last_name: Li - first_name: Dongxiao full_name: Yu, Dongxiao last_name: Yu - first_name: Huan full_name: Yang, Huan last_name: Yang - first_name: Jiguo full_name: Yu, Jiguo last_name: Yu - first_name: Holger full_name: Karl, Holger id: '126' last_name: Karl - first_name: Xiuzhen full_name: Cheng, Xiuzhen last_name: Cheng citation: ama: 'Li F, Yu D, Yang H, Yu J, Karl H, Cheng X. Multi-Armed-Bandit-Based Spectrum Scheduling Algorithms in Wireless Networks: A Survey. IEEE Wireless Communications. 2020:24-30. doi:10.1109/mwc.001.1900280' apa: 'Li, F., Yu, D., Yang, H., Yu, J., Karl, H., & Cheng, X. (2020). Multi-Armed-Bandit-Based Spectrum Scheduling Algorithms in Wireless Networks: A Survey. IEEE Wireless Communications, 24–30. https://doi.org/10.1109/mwc.001.1900280' bibtex: '@article{Li_Yu_Yang_Yu_Karl_Cheng_2020, title={Multi-Armed-Bandit-Based Spectrum Scheduling Algorithms in Wireless Networks: A Survey}, DOI={10.1109/mwc.001.1900280}, journal={IEEE Wireless Communications}, author={Li, Feng and Yu, Dongxiao and Yang, Huan and Yu, Jiguo and Karl, Holger and Cheng, Xiuzhen}, year={2020}, pages={24–30} }' chicago: 'Li, Feng, Dongxiao Yu, Huan Yang, Jiguo Yu, Holger Karl, and Xiuzhen Cheng. “Multi-Armed-Bandit-Based Spectrum Scheduling Algorithms in Wireless Networks: A Survey.” IEEE Wireless Communications, 2020, 24–30. https://doi.org/10.1109/mwc.001.1900280.' ieee: 'F. Li, D. Yu, H. Yang, J. Yu, H. Karl, and X. Cheng, “Multi-Armed-Bandit-Based Spectrum Scheduling Algorithms in Wireless Networks: A Survey,” IEEE Wireless Communications, pp. 24–30, 2020.' mla: 'Li, Feng, et al. “Multi-Armed-Bandit-Based Spectrum Scheduling Algorithms in Wireless Networks: A Survey.” IEEE Wireless Communications, 2020, pp. 24–30, doi:10.1109/mwc.001.1900280.' short: F. Li, D. Yu, H. Yang, J. Yu, H. Karl, X. Cheng, IEEE Wireless Communications (2020) 24–30. date_created: 2020-03-10T16:02:30Z date_updated: 2022-01-06T06:52:48Z department: - _id: '75' doi: 10.1109/mwc.001.1900280 language: - iso: eng page: 24-30 publication: IEEE Wireless Communications publication_identifier: issn: - 1536-1284 - 1558-0687 publication_status: published status: public title: 'Multi-Armed-Bandit-Based Spectrum Scheduling Algorithms in Wireless Networks: A Survey' type: journal_article user_id: '126' year: '2020' ... --- _id: '15025' abstract: - lang: eng text: In software engineering, the imprecise requirements of a user are transformed to a formal requirements specification during the requirements elicitation process. This process is usually guided by requirements engineers interviewing the user. We want to partially automate this first step of the software engineering process in order to enable users to specify a desired software system on their own. With our approach, users are only asked to provide exemplary behavioral descriptions. The problem of synthesizing a requirements specification from examples can partially be reduced to the problem of grammatical inference, to which we apply an active coevolutionary learning approach. However, this approach would usually require many feedback queries to be sent to the user. In this work, we extend and generalize our active learning approach to receive knowledge from multiple oracles, also known as proactive learning. The ‘user oracle’ represents input received from the user and the ‘knowledge oracle’ represents available, formalized domain knowledge. We call our two-oracle approach the ‘first apply knowledge then query’ (FAKT/Q) algorithm. We compare FAKT/Q to the active learning approach and provide an extensive benchmark evaluation. As result we find that the number of required user queries is reduced and the inference process is sped up significantly. Finally, with so-called On-The-Fly Markets, we present a motivation and an application of our approach where such knowledge is available. author: - first_name: Marcel Dominik full_name: Wever, Marcel Dominik id: '33176' last_name: Wever orcid: ' https://orcid.org/0000-0001-9782-6818' - first_name: Lorijn full_name: van Rooijen, Lorijn id: '58843' last_name: van Rooijen - first_name: Heiko full_name: Hamann, Heiko last_name: Hamann citation: ama: Wever MD, van Rooijen L, Hamann H. Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets. Evolutionary Computation. 2020;28(2):165–193. doi:10.1162/evco_a_00266 apa: Wever, M. D., van Rooijen, L., & Hamann, H. (2020). Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets. Evolutionary Computation, 28(2), 165–193. https://doi.org/10.1162/evco_a_00266 bibtex: '@article{Wever_van Rooijen_Hamann_2020, title={Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets}, volume={28}, DOI={10.1162/evco_a_00266}, number={2}, journal={Evolutionary Computation}, publisher={MIT Press Journals}, author={Wever, Marcel Dominik and van Rooijen, Lorijn and Hamann, Heiko}, year={2020}, pages={165–193} }' chicago: 'Wever, Marcel Dominik, Lorijn van Rooijen, and Heiko Hamann. “Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets.” Evolutionary Computation 28, no. 2 (2020): 165–193. https://doi.org/10.1162/evco_a_00266.' ieee: 'M. D. Wever, L. van Rooijen, and H. Hamann, “Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets,” Evolutionary Computation, vol. 28, no. 2, pp. 165–193, 2020, doi: 10.1162/evco_a_00266.' mla: Wever, Marcel Dominik, et al. “Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets.” Evolutionary Computation, vol. 28, no. 2, MIT Press Journals, 2020, pp. 165–193, doi:10.1162/evco_a_00266. short: M.D. Wever, L. van Rooijen, H. Hamann, Evolutionary Computation 28 (2020) 165–193. date_created: 2019-11-18T14:19:19Z date_updated: 2022-01-06T06:52:15Z department: - _id: '34' - _id: '355' - _id: '26' - _id: '63' - _id: '238' doi: 10.1162/evco_a_00266 intvolume: ' 28' issue: '2' language: - iso: eng page: 165–193 project: - _id: '1' name: SFB 901 - _id: '3' name: SFB 901 - Project Area B - _id: '9' name: SFB 901 - Subproject B1 - _id: '10' name: SFB 901 - Subproject B2 - _id: '52' name: Computing Resources Provided by the Paderborn Center for Parallel Computing publication: Evolutionary Computation publication_status: published publisher: MIT Press Journals related_material: link: - relation: confirmation url: https://www.mitpressjournals.org/doi/pdf/10.1162/evco_a_00266 status: public title: Multi-Oracle Coevolutionary Learning of Requirements Specifications from Examples in On-The-Fly Markets type: journal_article user_id: '15415' volume: 28 year: '2020' ... --- _id: '20766' abstract: - lang: eng text: Recently, the source separation performance was greatly improved by time-domain audio source separation based on dual-path recurrent neural network (DPRNN). DPRNN is a simple but effective model for a long sequential data. While DPRNN is quite efficient in modeling a sequential data of the length of an utterance, i.e., about 5 to 10 second data, it is harder to apply it to longer sequences such as whole conversations consisting of multiple utterances. It is simply because, in such a case, the number of time steps consumed by its internal module called inter-chunk RNN becomes extremely large. To mitigate this problem, this paper proposes a multi-path RNN (MPRNN), a generalized version of DPRNN, that models the input data in a hierarchical manner. In the MPRNN framework, the input data is represented at several (>_ 3) time-resolutions, each of which is modeled by a specific RNN sub-module. For example, the RNN sub-module that deals with the finest resolution may model temporal relationship only within a phoneme, while the RNN sub-module handling the most coarse resolution may capture only the relationship between utterances such as speaker information. We perform experiments using simulated dialogue-like mixtures and show that MPRNN has greater model capacity, and it outperforms the current state-of-the-art DPRNN framework especially in online processing scenarios. author: - first_name: Keisuke full_name: Kinoshita, Keisuke last_name: Kinoshita - first_name: Thilo full_name: von Neumann, Thilo id: '49870' last_name: von Neumann orcid: https://orcid.org/0000-0002-7717-8670 - first_name: Marc full_name: Delcroix, Marc last_name: Delcroix - first_name: Tomohiro full_name: Nakatani, Tomohiro last_name: Nakatani - first_name: Reinhold full_name: Haeb-Umbach, Reinhold id: '242' last_name: Haeb-Umbach citation: ama: 'Kinoshita K, von Neumann T, Delcroix M, Nakatani T, Haeb-Umbach R. Multi-Path RNN for Hierarchical Modeling of Long Sequential Data and its Application to Speaker Stream Separation. In: Proc. Interspeech 2020. ; 2020:2652-2656. doi:10.21437/Interspeech.2020-2388' apa: Kinoshita, K., von Neumann, T., Delcroix, M., Nakatani, T., & Haeb-Umbach, R. (2020). Multi-Path RNN for Hierarchical Modeling of Long Sequential Data and its Application to Speaker Stream Separation. Proc. Interspeech 2020, 2652–2656. https://doi.org/10.21437/Interspeech.2020-2388 bibtex: '@inproceedings{Kinoshita_von Neumann_Delcroix_Nakatani_Haeb-Umbach_2020, title={Multi-Path RNN for Hierarchical Modeling of Long Sequential Data and its Application to Speaker Stream Separation}, DOI={10.21437/Interspeech.2020-2388}, booktitle={Proc. Interspeech 2020}, author={Kinoshita, Keisuke and von Neumann, Thilo and Delcroix, Marc and Nakatani, Tomohiro and Haeb-Umbach, Reinhold}, year={2020}, pages={2652–2656} }' chicago: Kinoshita, Keisuke, Thilo von Neumann, Marc Delcroix, Tomohiro Nakatani, and Reinhold Haeb-Umbach. “Multi-Path RNN for Hierarchical Modeling of Long Sequential Data and Its Application to Speaker Stream Separation.” In Proc. Interspeech 2020, 2652–56, 2020. https://doi.org/10.21437/Interspeech.2020-2388. ieee: 'K. Kinoshita, T. von Neumann, M. Delcroix, T. Nakatani, and R. Haeb-Umbach, “Multi-Path RNN for Hierarchical Modeling of Long Sequential Data and its Application to Speaker Stream Separation,” in Proc. Interspeech 2020, 2020, pp. 2652–2656, doi: 10.21437/Interspeech.2020-2388.' mla: Kinoshita, Keisuke, et al. “Multi-Path RNN for Hierarchical Modeling of Long Sequential Data and Its Application to Speaker Stream Separation.” Proc. Interspeech 2020, 2020, pp. 2652–56, doi:10.21437/Interspeech.2020-2388. short: 'K. Kinoshita, T. von Neumann, M. Delcroix, T. Nakatani, R. Haeb-Umbach, in: Proc. Interspeech 2020, 2020, pp. 2652–2656.' date_created: 2020-12-16T14:15:24Z date_updated: 2023-11-15T12:14:25Z ddc: - '000' department: - _id: '54' doi: 10.21437/Interspeech.2020-2388 file: - access_level: open_access content_type: application/pdf creator: huesera date_created: 2020-12-16T14:16:32Z date_updated: 2020-12-16T14:16:32Z file_id: '20767' file_name: INTERSPEECH_2020_vonNeumann1_Paper.pdf file_size: 1725219 relation: main_file file_date_updated: 2020-12-16T14:16:32Z has_accepted_license: '1' language: - iso: eng oa: '1' page: 2652-2656 publication: Proc. Interspeech 2020 quality_controlled: '1' status: public title: Multi-Path RNN for Hierarchical Modeling of Long Sequential Data and its Application to Speaker Stream Separation type: conference user_id: '49870' year: '2020' ... --- _id: '20764' abstract: - lang: eng text: 'Most approaches to multi-talker overlapped speech separation and recognition assume that the number of simultaneously active speakers is given, but in realistic situations, it is typically unknown. To cope with this, we extend an iterative speech extraction system with mechanisms to count the number of sources and combine it with a single-talker speech recognizer to form the first end-to-end multi-talker automatic speech recognition system for an unknown number of active speakers. Our experiments show very promising performance in counting accuracy, source separation and speech recognition on simulated clean mixtures from WSJ0-2mix and WSJ0-3mix. Among others, we set a new state-of-the-art word error rate on the WSJ0-2mix database. Furthermore, our system generalizes well to a larger number of speakers than it ever saw during training, as shown in experiments with the WSJ0-4mix database. ' author: - first_name: Thilo full_name: von Neumann, Thilo id: '49870' last_name: von Neumann orcid: https://orcid.org/0000-0002-7717-8670 - first_name: Christoph full_name: Boeddeker, Christoph id: '40767' last_name: Boeddeker - first_name: Lukas full_name: Drude, Lukas last_name: Drude - first_name: Keisuke full_name: Kinoshita, Keisuke last_name: Kinoshita - first_name: Marc full_name: Delcroix, Marc last_name: Delcroix - first_name: Tomohiro full_name: Nakatani, Tomohiro last_name: Nakatani - first_name: Reinhold full_name: Haeb-Umbach, Reinhold id: '242' last_name: Haeb-Umbach citation: ama: 'von Neumann T, Boeddeker C, Drude L, et al. Multi-Talker ASR for an Unknown Number of Sources: Joint Training of Source Counting, Separation and ASR. In: Proc. Interspeech 2020. ; 2020:3097-3101. doi:10.21437/Interspeech.2020-2519' apa: 'von Neumann, T., Boeddeker, C., Drude, L., Kinoshita, K., Delcroix, M., Nakatani, T., & Haeb-Umbach, R. (2020). Multi-Talker ASR for an Unknown Number of Sources: Joint Training of Source Counting, Separation and ASR. Proc. Interspeech 2020, 3097–3101. https://doi.org/10.21437/Interspeech.2020-2519' bibtex: '@inproceedings{von Neumann_Boeddeker_Drude_Kinoshita_Delcroix_Nakatani_Haeb-Umbach_2020, title={Multi-Talker ASR for an Unknown Number of Sources: Joint Training of Source Counting, Separation and ASR}, DOI={10.21437/Interspeech.2020-2519}, booktitle={Proc. Interspeech 2020}, author={von Neumann, Thilo and Boeddeker, Christoph and Drude, Lukas and Kinoshita, Keisuke and Delcroix, Marc and Nakatani, Tomohiro and Haeb-Umbach, Reinhold}, year={2020}, pages={3097–3101} }' chicago: 'Neumann, Thilo von, Christoph Boeddeker, Lukas Drude, Keisuke Kinoshita, Marc Delcroix, Tomohiro Nakatani, and Reinhold Haeb-Umbach. “Multi-Talker ASR for an Unknown Number of Sources: Joint Training of Source Counting, Separation and ASR.” In Proc. Interspeech 2020, 3097–3101, 2020. https://doi.org/10.21437/Interspeech.2020-2519.' ieee: 'T. von Neumann et al., “Multi-Talker ASR for an Unknown Number of Sources: Joint Training of Source Counting, Separation and ASR,” in Proc. Interspeech 2020, 2020, pp. 3097–3101, doi: 10.21437/Interspeech.2020-2519.' mla: 'von Neumann, Thilo, et al. “Multi-Talker ASR for an Unknown Number of Sources: Joint Training of Source Counting, Separation and ASR.” Proc. Interspeech 2020, 2020, pp. 3097–101, doi:10.21437/Interspeech.2020-2519.' short: 'T. von Neumann, C. Boeddeker, L. Drude, K. Kinoshita, M. Delcroix, T. Nakatani, R. Haeb-Umbach, in: Proc. Interspeech 2020, 2020, pp. 3097–3101.' date_created: 2020-12-16T14:12:45Z date_updated: 2023-11-15T12:17:57Z ddc: - '000' department: - _id: '54' doi: 10.21437/Interspeech.2020-2519 file: - access_level: open_access content_type: application/pdf creator: huesera date_created: 2020-12-16T14:14:14Z date_updated: 2020-12-16T14:14:14Z file_id: '20765' file_name: INTERSPEECH_2020_vonNeumann_Paper.pdf file_size: 267893 relation: main_file file_date_updated: 2020-12-16T14:14:14Z has_accepted_license: '1' language: - iso: eng oa: '1' page: 3097-3101 project: - _id: '52' name: Computing Resources Provided by the Paderborn Center for Parallel Computing publication: Proc. Interspeech 2020 quality_controlled: '1' status: public title: 'Multi-Talker ASR for an Unknown Number of Sources: Joint Training of Source Counting, Separation and ASR' type: conference user_id: '49870' year: '2020' ...