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Spath, J. Gausemeier, R. Dumitrescu, J. Winter, S. Steglich, M. Drewel, in: A. Maier, J. Oehmen, P.E. Vermaas (Eds.),  Handbook of Engineering Systems Design, Springer, Cham, 2021, pp. 2–27.","apa":"Spath, D., Gausemeier, J., Dumitrescu, R., Winter, J., Steglich, S., &#38; Drewel, M. (2021). Digitalisation of Society. In A. Maier, J. Oehmen, &#38; P. E. Vermaas (Eds.), <i> Handbook of Engineering Systems Design</i> (pp. 2–27). Springer, Cham.","ama":"Spath D, Gausemeier J, Dumitrescu R, Winter J, Steglich S, Drewel M. Digitalisation of Society. In: Maier A, Oehmen J, Vermaas PE, eds. <i> Handbook of Engineering Systems Design</i>. Springer, Cham; 2021:2-27.","chicago":"Spath, Dieter, Jürgen Gausemeier, Roman Dumitrescu, Johannes Winter, Steffen Steglich, and Marvin Drewel. “Digitalisation of Society.” In <i> Handbook of Engineering Systems Design</i>, edited by Anja Maier, Josef Oehmen, and Pieter E. Vermaas, 2–27. Springer, Cham, 2021.","ieee":"D. Spath, J. Gausemeier, R. 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Springer, Cham, 2021, pp. 2–27."},"page":"2-27","year":"2021","date_created":"2021-11-16T14:09:25Z","author":[{"first_name":"Dieter","last_name":"Spath","full_name":"Spath, Dieter"},{"first_name":"Jürgen","full_name":"Gausemeier, Jürgen","id":"163","last_name":"Gausemeier"},{"first_name":"Roman","full_name":"Dumitrescu, Roman","id":"16190","last_name":"Dumitrescu"},{"last_name":"Winter","full_name":"Winter, Johannes","first_name":"Johannes"},{"last_name":"Steglich","full_name":"Steglich, Steffen","first_name":"Steffen"},{"last_name":"Drewel","full_name":"Drewel, Marvin","first_name":"Marvin"}],"publisher":"Springer, Cham","date_updated":"2022-01-06T06:57:40Z","title":"Digitalisation of Society"},{"user_id":"11829","department":[{"_id":"49"}],"project":[{"name":"Vermiedene Kreuzungen von Lamb-Wellenmoden in mehrlagigen Strukturen","_id":"105","grant_number":"449607253"}],"_id":"27847","alternative_title":["Über die Bestimmung der Festigkeit der Klebeschicht in mehrschichtigen Materialien durch Untersuchung des modalen Abstands von geführten elastischen Wellen"],"language":[{"iso":"eng"}],"file_date_updated":"2021-11-26T07:53:21Z","ddc":["620"],"type":"conference","publication":"МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ В ЕСТЕСТВЕННЫХ НАУКАХ - XXX Всероссийская школа-конференция","file":[{"file_id":"27848","access_level":"open_access","file_name":"Paper - Mode Repulsion - 2021 MMEN (Perm).pdf","file_size":450749,"date_created":"2021-11-25T14:57:25Z","creator":"leanderc","date_updated":"2021-11-26T07:53:21Z","relation":"main_file","content_type":"application/pdf"}],"status":"public","author":[{"first_name":"Yevgeniya","full_name":"Lugovtsova, Yevgeniya","last_name":"Lugovtsova"},{"first_name":"Henning","last_name":"Zeipert","id":"32580","full_name":"Zeipert, Henning"},{"id":"29190","full_name":"Johannesmann, Sarah","last_name":"Johannesmann","first_name":"Sarah"},{"first_name":"Marcel","full_name":"Nicolai, Marcel","last_name":"Nicolai"},{"last_name":"Prager","full_name":"Prager, Jens","first_name":"Jens"},{"full_name":"Henning, Bernd","id":"213","last_name":"Henning","first_name":"Bernd"}],"date_created":"2021-11-25T14:58:13Z","oa":"1","date_updated":"2022-01-06T06:57:47Z","conference":{"location":"Perm","end_date":"2021-10-09","start_date":"2021-10-06","name":"МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ В ЕСТЕСТВЕННЫХ НАУКАХ - XXX Всероссийская школа-конференция"},"title":"К ОПРЕДЕЛЕНИЮ ПРОЧНОСТИ КЛЕЕВОГО СОЕДИНЕНИЯ В МНОГОСЛОЙНЫХ МАТЕРИАЛАХ ПУТЕМ ИССЛЕДОВАНИЯ ОБЛАСТЕЙ РАСТАЛКИВАНИЯ БЕГУЩИХ УПРУГИХ ВОЛН","has_accepted_license":"1","citation":{"apa":"Lugovtsova, Y., Zeipert, H., Johannesmann, S., Nicolai, M., Prager, J., &#38; Henning, B. (2021). К ОПРЕДЕЛЕНИЮ ПРОЧНОСТИ КЛЕЕВОГО СОЕДИНЕНИЯ В МНОГОСЛОЙНЫХ МАТЕРИАЛАХ ПУТЕМ ИССЛЕДОВАНИЯ ОБЛАСТЕЙ РАСТАЛКИВАНИЯ БЕГУЩИХ УПРУГИХ ВОЛН. <i>МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ В ЕСТЕСТВЕННЫХ НАУКАХ - XXX Всероссийская Школа-Конференция</i>. МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ В ЕСТЕСТВЕННЫХ НАУКАХ - XXX Всероссийская школа-конференция, Perm.","short":"Y. Lugovtsova, H. Zeipert, S. Johannesmann, M. Nicolai, J. Prager, B. Henning, in: МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ В ЕСТЕСТВЕННЫХ НАУКАХ - XXX Всероссийская Школа-Конференция, Perm, 2021.","bibtex":"@inproceedings{Lugovtsova_Zeipert_Johannesmann_Nicolai_Prager_Henning_2021, place={Perm}, title={К ОПРЕДЕЛЕНИЮ ПРОЧНОСТИ КЛЕЕВОГО СОЕДИНЕНИЯ В МНОГОСЛОЙНЫХ МАТЕРИАЛАХ ПУТЕМ ИССЛЕДОВАНИЯ ОБЛАСТЕЙ РАСТАЛКИВАНИЯ БЕГУЩИХ УПРУГИХ ВОЛН}, booktitle={МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ В ЕСТЕСТВЕННЫХ НАУКАХ - XXX Всероссийская школа-конференция}, author={Lugovtsova, Yevgeniya and Zeipert, Henning and Johannesmann, Sarah and Nicolai, Marcel and Prager, Jens and Henning, Bernd}, year={2021} }","mla":"Lugovtsova, Yevgeniya, et al. “К ОПРЕДЕЛЕНИЮ ПРОЧНОСТИ КЛЕЕВОГО СОЕДИНЕНИЯ В МНОГОСЛОЙНЫХ МАТЕРИАЛАХ ПУТЕМ ИССЛЕДОВАНИЯ ОБЛАСТЕЙ РАСТАЛКИВАНИЯ БЕГУЩИХ УПРУГИХ ВОЛН.” <i>МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ В ЕСТЕСТВЕННЫХ НАУКАХ - XXX Всероссийская Школа-Конференция</i>, 2021.","chicago":"Lugovtsova, Yevgeniya, Henning Zeipert, Sarah Johannesmann, Marcel Nicolai, Jens Prager, and Bernd Henning. “К ОПРЕДЕЛЕНИЮ ПРОЧНОСТИ КЛЕЕВОГО СОЕДИНЕНИЯ В МНОГОСЛОЙНЫХ МАТЕРИАЛАХ ПУТЕМ ИССЛЕДОВАНИЯ ОБЛАСТЕЙ РАСТАЛКИВАНИЯ БЕГУЩИХ УПРУГИХ ВОЛН.” In <i>МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ В ЕСТЕСТВЕННЫХ НАУКАХ - XXX Всероссийская Школа-Конференция</i>. Perm, 2021.","ieee":"Y. Lugovtsova, H. Zeipert, S. Johannesmann, M. Nicolai, J. Prager, and B. Henning, “К ОПРЕДЕЛЕНИЮ ПРОЧНОСТИ КЛЕЕВОГО СОЕДИНЕНИЯ В МНОГОСЛОЙНЫХ МАТЕРИАЛАХ ПУТЕМ ИССЛЕДОВАНИЯ ОБЛАСТЕЙ РАСТАЛКИВАНИЯ БЕГУЩИХ УПРУГИХ ВОЛН,” presented at the МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ В ЕСТЕСТВЕННЫХ НАУКАХ - XXX Всероссийская школа-конференция, Perm, 2021.","ama":"Lugovtsova Y, Zeipert H, Johannesmann S, Nicolai M, Prager J, Henning B. К ОПРЕДЕЛЕНИЮ ПРОЧНОСТИ КЛЕЕВОГО СОЕДИНЕНИЯ В МНОГОСЛОЙНЫХ МАТЕРИАЛАХ ПУТЕМ ИССЛЕДОВАНИЯ ОБЛАСТЕЙ РАСТАЛКИВАНИЯ БЕГУЩИХ УПРУГИХ ВОЛН. In: <i>МАТЕМАТИЧЕСКОЕ МОДЕЛИРОВАНИЕ В ЕСТЕСТВЕННЫХ НАУКАХ - XXX Всероссийская Школа-Конференция</i>. ; 2021."},"year":"2021","place":"Perm"},{"keyword":["Automated Machine Learning","Multi Label Classification","Hierarchical Planning","Bayesian Optimization"],"language":[{"iso":"eng"}],"project":[{"name":"SFB 901","_id":"1"},{"name":"SFB 901 - Project Area B","_id":"3"},{"_id":"10","name":"SFB 901 - Subproject B2"},{"name":"Computing Resources Provided by the Paderborn Center for Parallel Computing","_id":"52"}],"_id":"21004","user_id":"5786","department":[{"_id":"34"},{"_id":"355"},{"_id":"26"}],"abstract":[{"text":"Automated machine learning (AutoML) supports the algorithmic construction and data-specific customization of machine learning pipelines, including the selection, combination, and parametrization of machine learning algorithms as main constituents. Generally speaking, AutoML approaches comprise two major components: a search space model and an optimizer for traversing the space. Recent approaches have shown impressive results in the realm of supervised learning, most notably (single-label) classification (SLC). Moreover, first attempts at extending these approaches towards multi-label classification (MLC) have been made. While the space of candidate pipelines is already huge in SLC, the complexity of the search space is raised to an even higher power in MLC. One may wonder, therefore, whether and to what extent optimizers established for SLC can scale to this increased complexity, and how they compare to each other. This paper makes the following contributions: First, we survey existing approaches to AutoML for MLC. Second, we augment these approaches with optimizers not previously tried for MLC. Third, we propose a benchmarking framework that supports a fair and systematic comparison. Fourth, we conduct an extensive experimental study, evaluating the methods on a suite of MLC problems. We find a grammar-based best-first search to compare favorably to other optimizers.","lang":"eng"}],"status":"public","type":"journal_article","publication":"IEEE Transactions on Pattern Analysis and Machine Intelligence","title":"AutoML for Multi-Label Classification: Overview and Empirical Evaluation","doi":"10.1109/tpami.2021.3051276","date_updated":"2022-01-06T06:54:42Z","date_created":"2021-01-16T14:48:13Z","author":[{"first_name":"Marcel Dominik","orcid":" https://orcid.org/0000-0001-9782-6818","last_name":"Wever","id":"33176","full_name":"Wever, Marcel Dominik"},{"last_name":"Tornede","full_name":"Tornede, Alexander","id":"38209","first_name":"Alexander"},{"full_name":"Mohr, Felix","last_name":"Mohr","first_name":"Felix"},{"full_name":"Hüllermeier, Eyke","id":"48129","last_name":"Hüllermeier","first_name":"Eyke"}],"year":"2021","citation":{"apa":"Wever, M. D., Tornede, A., Mohr, F., &#38; Hüllermeier, E. (2021). AutoML for Multi-Label Classification: Overview and Empirical Evaluation. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, 1–1. <a href=\"https://doi.org/10.1109/tpami.2021.3051276\">https://doi.org/10.1109/tpami.2021.3051276</a>","mla":"Wever, Marcel Dominik, et al. “AutoML for Multi-Label Classification: Overview and Empirical Evaluation.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, 2021, pp. 1–1, doi:<a href=\"https://doi.org/10.1109/tpami.2021.3051276\">10.1109/tpami.2021.3051276</a>.","bibtex":"@article{Wever_Tornede_Mohr_Hüllermeier_2021, title={AutoML for Multi-Label Classification: Overview and Empirical Evaluation}, DOI={<a href=\"https://doi.org/10.1109/tpami.2021.3051276\">10.1109/tpami.2021.3051276</a>}, journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, author={Wever, Marcel Dominik and Tornede, Alexander and Mohr, Felix and Hüllermeier, Eyke}, year={2021}, pages={1–1} }","short":"M.D. Wever, A. Tornede, F. Mohr, E. Hüllermeier, IEEE Transactions on Pattern Analysis and Machine Intelligence (2021) 1–1.","ama":"Wever MD, Tornede A, Mohr F, Hüllermeier E. AutoML for Multi-Label Classification: Overview and Empirical Evaluation. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>. Published online 2021:1-1. doi:<a href=\"https://doi.org/10.1109/tpami.2021.3051276\">10.1109/tpami.2021.3051276</a>","ieee":"M. D. Wever, A. Tornede, F. Mohr, and E. Hüllermeier, “AutoML for Multi-Label Classification: Overview and Empirical Evaluation,” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, pp. 1–1, 2021, doi: <a href=\"https://doi.org/10.1109/tpami.2021.3051276\">10.1109/tpami.2021.3051276</a>.","chicago":"Wever, Marcel Dominik, Alexander Tornede, Felix Mohr, and Eyke Hüllermeier. “AutoML for Multi-Label Classification: Overview and Empirical Evaluation.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, 2021, 1–1. <a href=\"https://doi.org/10.1109/tpami.2021.3051276\">https://doi.org/10.1109/tpami.2021.3051276</a>."},"page":"1-1","publication_status":"published","publication_identifier":{"issn":["0162-8828","2160-9292","1939-3539"]}},{"department":[{"_id":"75"}],"user_id":"63288","_id":"21005","project":[{"name":"SFB 901 - Subproject C4","_id":"16"},{"_id":"4","name":"SFB 901 - Project Area C"},{"name":"SFB 901","_id":"1"}],"status":"public","type":"conference","conference":{"end_date":"2021-05-13","location":"Vancouver BC Canada","name":"IEEE INFOCOM 2021 - IEEE Conference on Computer Communications","start_date":"2021-05-10"},"doi":"10.1109/INFOCOMWKSHPS51825.2021.9484599","main_file_link":[{"url":"https://ieeexplore.ieee.org/document/9484599"}],"author":[{"first_name":"Asif","last_name":"Hasnain","full_name":"Hasnain, Asif","id":"63288"},{"first_name":"Holger","id":"126","full_name":"Karl, Holger","last_name":"Karl"}],"date_updated":"2022-01-06T06:54:42Z","citation":{"ama":"Hasnain A, Karl H. Learning Coflow Admissions. In: <i>IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)</i>. IEEE Communications Society. doi:<a href=\"https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484599\">10.1109/INFOCOMWKSHPS51825.2021.9484599</a>","ieee":"A. Hasnain and H. Karl, “Learning Coflow Admissions,” in <i>IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)</i>, Vancouver BC Canada.","chicago":"Hasnain, Asif, and Holger Karl. “Learning Coflow Admissions.” In <i>IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)</i>. IEEE Communications Society, n.d. <a href=\"https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484599\">https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484599</a>.","bibtex":"@inproceedings{Hasnain_Karl, title={Learning Coflow Admissions}, DOI={<a href=\"https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484599\">10.1109/INFOCOMWKSHPS51825.2021.9484599</a>}, booktitle={IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)}, publisher={IEEE Communications Society}, author={Hasnain, Asif and Karl, Holger} }","short":"A. Hasnain, H. Karl, in: IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), IEEE Communications Society, n.d.","mla":"Hasnain, Asif, and Holger Karl. “Learning Coflow Admissions.” <i>IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)</i>, IEEE Communications Society, doi:<a href=\"https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484599\">10.1109/INFOCOMWKSHPS51825.2021.9484599</a>.","apa":"Hasnain, A., &#38; Karl, H. (n.d.). Learning Coflow Admissions. In <i>IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)</i>. Vancouver BC Canada: IEEE Communications Society. <a href=\"https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484599\">https://doi.org/10.1109/INFOCOMWKSHPS51825.2021.9484599</a>"},"related_material":{"link":[{"url":"https://ieeexplore.ieee.org/document/9484599","relation":"confirmation"}]},"publication_status":"accepted","language":[{"iso":"eng"}],"keyword":["Coflow scheduling","Reinforcement learning","Deadlines"],"ddc":["000"],"abstract":[{"lang":"eng","text":"Data-parallel applications are developed using different data programming models, e.g., MapReduce, partition/aggregate. These models represent diverse resource requirements of application in a datacenter network, which can be represented by the coflow abstraction. The conventional method of creating hand-crafted coflow heuristics for admission or scheduling for different workloads is practically infeasible. In this paper, we propose a deep reinforcement learning (DRL)-based coflow admission scheme -- LCS -- that can learn an admission policy for a higher-level performance objective, i.e., maximize successful coflow admissions, without manual feature engineering.  LCS is trained on a production trace, which has online coflow arrivals. The evaluation results show that LCS is able to learn a reasonable admission policy that admits more coflows than state-of-the-art Varys heuristic while meeting their deadlines."}],"publication":"IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","title":"Learning Coflow Admissions","date_created":"2021-01-16T18:24:19Z","publisher":"IEEE Communications Society","year":"2021"},{"title":"Far-Field Automatic Speech Recognition","date_created":"2021-01-25T08:15:27Z","year":"2021","issue":"2","language":[{"iso":"eng"}],"ddc":["000"],"file":[{"date_updated":"2021-01-25T08:17:23Z","creator":"huesera","date_created":"2021-01-25T08:17:23Z","file_size":4173988,"access_level":"open_access","file_name":"proceedings_2021_haebumbach_Paper.pdf","file_id":"21066","content_type":"application/pdf","relation":"main_file"}],"abstract":[{"lang":"eng","text":"The machine recognition of speech spoken at a distance from the microphones, known as far-field automatic speech recognition (ASR), has received a significant increase of attention in science and industry, which caused or was caused by an equally significant improvement in recognition accuracy. Meanwhile it has entered the consumer market with digital home assistants with a spoken language interface being its most prominent application. Speech recorded at a distance is affected by various acoustic distortions and, consequently, quite different processing pipelines have emerged compared to ASR for close-talk speech. A signal enhancement front-end for dereverberation, source separation and acoustic beamforming is employed to clean up the speech, and the back-end ASR engine is robustified by multi-condition training and adaptation. We will also describe the so-called end-to-end approach to ASR, which is a new promising architecture that has recently been extended to the far-field scenario. This tutorial article gives an account of the algorithms used to enable accurate speech recognition from a distance, and it will be seen that, although deep learning has a significant share in the technological breakthroughs, a clever combination with traditional signal processing can lead to surprisingly effective solutions."}],"publication":"Proceedings of the IEEE","doi":"10.1109/JPROC.2020.3018668","author":[{"id":"242","full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","first_name":"Reinhold"},{"full_name":"Heymann, Jahn","last_name":"Heymann","first_name":"Jahn"},{"first_name":"Lukas","full_name":"Drude, Lukas","last_name":"Drude"},{"last_name":"Watanabe","full_name":"Watanabe, Shinji","first_name":"Shinji"},{"first_name":"Marc","full_name":"Delcroix, Marc","last_name":"Delcroix"},{"last_name":"Nakatani","full_name":"Nakatani, Tomohiro","first_name":"Tomohiro"}],"volume":109,"oa":"1","date_updated":"2022-01-06T06:54:44Z","citation":{"chicago":"Haeb-Umbach, Reinhold, Jahn Heymann, Lukas Drude, Shinji Watanabe, Marc Delcroix, and Tomohiro Nakatani. “Far-Field Automatic Speech Recognition.” <i>Proceedings of the IEEE</i> 109, no. 2 (2021): 124–48. <a href=\"https://doi.org/10.1109/JPROC.2020.3018668\">https://doi.org/10.1109/JPROC.2020.3018668</a>.","ieee":"R. Haeb-Umbach, J. Heymann, L. Drude, S. Watanabe, M. Delcroix, and T. Nakatani, “Far-Field Automatic Speech Recognition,” <i>Proceedings of the IEEE</i>, vol. 109, no. 2, pp. 124–148, 2021.","ama":"Haeb-Umbach R, Heymann J, Drude L, Watanabe S, Delcroix M, Nakatani T. Far-Field Automatic Speech Recognition. <i>Proceedings of the IEEE</i>. 2021;109(2):124-148. doi:<a href=\"https://doi.org/10.1109/JPROC.2020.3018668\">10.1109/JPROC.2020.3018668</a>","apa":"Haeb-Umbach, R., Heymann, J., Drude, L., Watanabe, S., Delcroix, M., &#38; Nakatani, T. (2021). Far-Field Automatic Speech Recognition. <i>Proceedings of the IEEE</i>, <i>109</i>(2), 124–148. <a href=\"https://doi.org/10.1109/JPROC.2020.3018668\">https://doi.org/10.1109/JPROC.2020.3018668</a>","bibtex":"@article{Haeb-Umbach_Heymann_Drude_Watanabe_Delcroix_Nakatani_2021, title={Far-Field Automatic Speech Recognition}, volume={109}, DOI={<a href=\"https://doi.org/10.1109/JPROC.2020.3018668\">10.1109/JPROC.2020.3018668</a>}, number={2}, journal={Proceedings of the IEEE}, author={Haeb-Umbach, Reinhold and Heymann, Jahn and Drude, Lukas and Watanabe, Shinji and Delcroix, Marc and Nakatani, Tomohiro}, year={2021}, pages={124–148} }","mla":"Haeb-Umbach, Reinhold, et al. “Far-Field Automatic Speech Recognition.” <i>Proceedings of the IEEE</i>, vol. 109, no. 2, 2021, pp. 124–48, doi:<a href=\"https://doi.org/10.1109/JPROC.2020.3018668\">10.1109/JPROC.2020.3018668</a>.","short":"R. Haeb-Umbach, J. Heymann, L. Drude, S. Watanabe, M. Delcroix, T. Nakatani, Proceedings of the IEEE 109 (2021) 124–148."},"intvolume":"       109","page":"124-148","has_accepted_license":"1","file_date_updated":"2021-01-25T08:17:23Z","user_id":"59789","department":[{"_id":"54"}],"project":[{"name":"Computing Resources Provided by the Paderborn Center for Parallel Computing","_id":"52"}],"_id":"21065","status":"public","type":"journal_article"},{"title":"Investigating peculiarities of piezoelectric detection methods for acoustic plate waves in material characterisation applications","doi":"10.1515/teme-2020-0098","date_updated":"2022-01-06T06:54:44Z","volume":88,"author":[{"first_name":"Leander","last_name":"Claes","orcid":"0000-0002-4393-268X","full_name":"Claes, Leander","id":"11829"},{"first_name":"Hanna","last_name":"Schmiegel","full_name":"Schmiegel, Hanna"},{"last_name":"Grünsteidl","full_name":"Grünsteidl, Clemens","first_name":"Clemens"},{"first_name":"Sarah","full_name":"Johannesmann, Sarah","id":"29190","last_name":"Johannesmann"},{"first_name":"Manuel","id":"11289","full_name":"Webersen, Manuel","last_name":"Webersen","orcid":"0000-0001-6411-4232"},{"first_name":"Bernd","last_name":"Henning","full_name":"Henning, Bernd","id":"213"}],"date_created":"2021-01-25T09:38:58Z","year":"2021","intvolume":"        88","page":"147-155","citation":{"mla":"Claes, Leander, et al. “Investigating Peculiarities of Piezoelectric Detection Methods for Acoustic Plate Waves in Material Characterisation Applications.” <i>Tm - Technisches Messen</i>, vol. 88, no. 3, 2021, pp. 147–55, doi:<a href=\"https://doi.org/10.1515/teme-2020-0098\">10.1515/teme-2020-0098</a>.","short":"L. Claes, H. Schmiegel, C. Grünsteidl, S. Johannesmann, M. Webersen, B. Henning, Tm - Technisches Messen 88 (2021) 147–155.","bibtex":"@article{Claes_Schmiegel_Grünsteidl_Johannesmann_Webersen_Henning_2021, title={Investigating peculiarities of piezoelectric detection methods for acoustic plate waves in material characterisation applications}, volume={88}, DOI={<a href=\"https://doi.org/10.1515/teme-2020-0098\">10.1515/teme-2020-0098</a>}, number={3}, journal={tm - Technisches Messen}, author={Claes, Leander and Schmiegel, Hanna and Grünsteidl, Clemens and Johannesmann, Sarah and Webersen, Manuel and Henning, Bernd}, year={2021}, pages={147–155} }","apa":"Claes, L., Schmiegel, H., Grünsteidl, C., Johannesmann, S., Webersen, M., &#38; Henning, B. (2021). Investigating peculiarities of piezoelectric detection methods for acoustic plate waves in material characterisation applications. <i>Tm - Technisches Messen</i>, <i>88</i>(3), 147–155. <a href=\"https://doi.org/10.1515/teme-2020-0098\">https://doi.org/10.1515/teme-2020-0098</a>","ama":"Claes L, Schmiegel H, Grünsteidl C, Johannesmann S, Webersen M, Henning B. Investigating peculiarities of piezoelectric detection methods for acoustic plate waves in material characterisation applications. <i>tm - Technisches Messen</i>. 2021;88(3):147-155. doi:<a href=\"https://doi.org/10.1515/teme-2020-0098\">10.1515/teme-2020-0098</a>","chicago":"Claes, Leander, Hanna Schmiegel, Clemens Grünsteidl, Sarah Johannesmann, Manuel Webersen, and Bernd Henning. “Investigating Peculiarities of Piezoelectric Detection Methods for Acoustic Plate Waves in Material Characterisation Applications.” <i>Tm - Technisches Messen</i> 88, no. 3 (2021): 147–55. <a href=\"https://doi.org/10.1515/teme-2020-0098\">https://doi.org/10.1515/teme-2020-0098</a>.","ieee":"L. Claes, H. Schmiegel, C. Grünsteidl, S. Johannesmann, M. Webersen, and B. Henning, “Investigating peculiarities of piezoelectric detection methods for acoustic plate waves in material characterisation applications,” <i>tm - Technisches Messen</i>, vol. 88, no. 3, pp. 147–155, 2021."},"publication_identifier":{"issn":["2196-7113","0171-8096"]},"publication_status":"published","issue":"3","language":[{"iso":"eng"}],"alternative_title":["Untersuchung von Eigenheiten piezoelektrischer Detektionsmethoden für akustische Plattenwellen zur Materialcharakterisierung"],"_id":"21067","project":[{"grant_number":"449607253","_id":"105","name":"Vermiedene Kreuzungen von Lamb-Wellenmoden in mehrlagigen Strukturen"}],"department":[{"_id":"49"}],"user_id":"11829","abstract":[{"text":"Acoustic waves in plates have proven a viable tool for testing and material characterisation purposes. There are a multitude of options for excitation and detection of theses waves, such as optical and piezoelectric systems. While optical systems, with thermoelastic excitation and interferometric detection, have the benefit of being contactless, they usually require rather complex and expensive experimental setups. Piezoelectric systems are more easily realised but require direct contact with the specimen and usually have a limited bandwidth, especially in case of piezoelectric excitation. In this work, the authors compare the properties of piezoelectric and optical detection methods for broad-band acoustic signals. The shape (e. g. the displacement) of a propagating plate wave is given by its frequency and wave number, allowing to investigate correlations between mode shapes and received signal strengths. This is aided by evaluations in normalised frequency and wavenumber space, facilitating comparisons of different specimens. Further, the authors explore possibilities to utilise the specific properties of the detection methods to determine acoustic material parameters.","lang":"eng"}],"status":"public","publication":"tm - Technisches Messen","type":"journal_article"},{"year":"2021","citation":{"chicago":"Itner, Dominik, Hauke Gravenkamp, Dmitrij Dreiling, Nadine Feldmann, and Bernd Henning. “Simulation of Guided Waves in Cylinders Subject to Arbitrary Boundary Conditions for Applications in Material Characterization.” <i>PAMM</i>, 2021. <a href=\"https://doi.org/10.1002/pamm.202000232\">https://doi.org/10.1002/pamm.202000232</a>.","ieee":"D. Itner, H. Gravenkamp, D. Dreiling, N. Feldmann, and B. Henning, “Simulation of guided waves in cylinders subject to arbitrary boundary conditions for applications in material characterization,” <i>PAMM</i>, 2021.","ama":"Itner D, Gravenkamp H, Dreiling D, Feldmann N, Henning B. Simulation of guided waves in cylinders subject to arbitrary boundary conditions for applications in material characterization. <i>PAMM</i>. 2021. doi:<a href=\"https://doi.org/10.1002/pamm.202000232\">10.1002/pamm.202000232</a>","mla":"Itner, Dominik, et al. “Simulation of Guided Waves in Cylinders Subject to Arbitrary Boundary Conditions for Applications in Material Characterization.” <i>PAMM</i>, 2021, doi:<a href=\"https://doi.org/10.1002/pamm.202000232\">10.1002/pamm.202000232</a>.","bibtex":"@article{Itner_Gravenkamp_Dreiling_Feldmann_Henning_2021, title={Simulation of guided waves in cylinders subject to arbitrary boundary conditions for applications in material characterization}, DOI={<a href=\"https://doi.org/10.1002/pamm.202000232\">10.1002/pamm.202000232</a>}, journal={PAMM}, author={Itner, Dominik and Gravenkamp, Hauke and Dreiling, Dmitrij and Feldmann, Nadine and Henning, Bernd}, year={2021} }","short":"D. Itner, H. Gravenkamp, D. Dreiling, N. Feldmann, B. Henning, PAMM (2021).","apa":"Itner, D., Gravenkamp, H., Dreiling, D., Feldmann, N., &#38; Henning, B. (2021). Simulation of guided waves in cylinders subject to arbitrary boundary conditions for applications in material characterization. <i>PAMM</i>. <a href=\"https://doi.org/10.1002/pamm.202000232\">https://doi.org/10.1002/pamm.202000232</a>"},"publication_identifier":{"issn":["1617-7061","1617-7061"]},"publication_status":"published","title":"Simulation of guided waves in cylinders subject to arbitrary boundary conditions for applications in material characterization","doi":"10.1002/pamm.202000232","date_updated":"2022-01-06T06:54:44Z","author":[{"first_name":"Dominik","full_name":"Itner, Dominik","last_name":"Itner"},{"first_name":"Hauke","last_name":"Gravenkamp","full_name":"Gravenkamp, Hauke"},{"first_name":"Dmitrij","last_name":"Dreiling","full_name":"Dreiling, Dmitrij","id":"32616"},{"first_name":"Nadine","last_name":"Feldmann","id":"23082","full_name":"Feldmann, Nadine"},{"first_name":"Bernd","id":"213","full_name":"Henning, Bernd","last_name":"Henning"}],"date_created":"2021-01-26T13:52:47Z","status":"public","publication":"PAMM","type":"journal_article","language":[{"iso":"eng"}],"_id":"21082","project":[{"_id":"89","name":"Vollständige Bestimmung der akustischen Materialparameter von Polymeren","grant_number":"409779252"}],"department":[{"_id":"49"}],"user_id":"23082"},{"title":"Derandomization and Local Graph Problems in the Node-Capacitated Clique","date_created":"2021-01-26T13:58:14Z","supervisor":[{"last_name":"Scheideler","full_name":"Scheideler, Christian","id":"20792","first_name":"Christian"}],"author":[{"first_name":"Julian","last_name":"Werthmann","id":"50024","full_name":"Werthmann, Julian"}],"date_updated":"2022-01-06T06:54:44Z","citation":{"ama":"Werthmann J. <i>Derandomization and Local Graph Problems in the Node-Capacitated Clique</i>.; 2021.","chicago":"Werthmann, Julian. <i>Derandomization and Local Graph Problems in the Node-Capacitated Clique</i>, 2021.","ieee":"J. Werthmann, <i>Derandomization and Local Graph Problems in the Node-Capacitated Clique</i>. 2021.","short":"J. Werthmann, Derandomization and Local Graph Problems in the Node-Capacitated Clique, 2021.","bibtex":"@book{Werthmann_2021, title={Derandomization and Local Graph Problems in the Node-Capacitated Clique}, author={Werthmann, Julian}, year={2021} }","mla":"Werthmann, Julian. <i>Derandomization and Local Graph Problems in the Node-Capacitated Clique</i>. 2021.","apa":"Werthmann, J. (2021). <i>Derandomization and Local Graph Problems in the Node-Capacitated Clique</i>."},"year":"2021","language":[{"iso":"eng"}],"department":[{"_id":"79"}],"user_id":"15504","_id":"21084","project":[{"name":"SFB 901","_id":"1"},{"name":"SFB 901 - Project Area A","_id":"2"},{"_id":"5","name":"SFB 901 - Subproject A1"}],"status":"public","type":"mastersthesis"},{"publication_status":"accepted","year":"2021","citation":{"short":"F. Mohr, M.D. Wever, A. Tornede, E. Hüllermeier, IEEE Transactions on Pattern Analysis and Machine Intelligence (n.d.).","mla":"Mohr, Felix, et al. “Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, IEEE.","bibtex":"@article{Mohr_Wever_Tornede_Hüllermeier, title={Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning}, journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, publisher={IEEE}, author={Mohr, Felix and Wever, Marcel Dominik and Tornede, Alexander and Hüllermeier, Eyke} }","apa":"Mohr, F., Wever, M. D., Tornede, A., &#38; Hüllermeier, E. (n.d.). Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>.","ama":"Mohr F, Wever MD, Tornede A, Hüllermeier E. Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning. <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>.","ieee":"F. Mohr, M. D. Wever, A. Tornede, and E. Hüllermeier, “Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning,” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>.","chicago":"Mohr, Felix, Marcel Dominik Wever, Alexander Tornede, and Eyke Hüllermeier. “Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning.” <i>IEEE Transactions on Pattern Analysis and Machine Intelligence</i>, n.d."},"date_updated":"2022-01-06T06:54:45Z","publisher":"IEEE","author":[{"first_name":"Felix","last_name":"Mohr","full_name":"Mohr, Felix"},{"first_name":"Marcel Dominik","id":"33176","full_name":"Wever, Marcel Dominik","orcid":" https://orcid.org/0000-0001-9782-6818","last_name":"Wever"},{"full_name":"Tornede, Alexander","id":"38209","last_name":"Tornede","first_name":"Alexander"},{"id":"48129","full_name":"Hüllermeier, Eyke","last_name":"Hüllermeier","first_name":"Eyke"}],"date_created":"2021-01-27T13:45:52Z","title":"Predicting Machine Learning Pipeline Runtimes in the Context of Automated Machine Learning","publication":"IEEE Transactions on Pattern Analysis and Machine Intelligence","type":"journal_article","abstract":[{"lang":"eng","text":"Automated Machine Learning (AutoML) seeks to automatically find so-called machine learning pipelines that maximize the prediction performance when being used to train a model on a given dataset. One of the main and yet open challenges in AutoML is an effective use of computational resources: An AutoML process involves the evaluation of many candidate pipelines, which   are costly but often ineffective because they are canceled due to a timeout.\r\nIn this paper, we present an approach to predict the runtime of two-step machine learning pipelines with up to one pre-processor, which can be used to anticipate whether or not a pipeline will time out. Separate runtime models are trained offline for each algorithm that may be used in a pipeline, and an overall prediction is derived from these models. We empirically show that the approach increases successful evaluations made by an AutoML tool while preserving or even improving on the previously best solutions."}],"status":"public","_id":"21092","project":[{"name":"SFB 901","_id":"1"},{"_id":"3","name":"SFB 901 - Project Area B"},{"name":"SFB 901 - Subproject B2","_id":"10"},{"name":"Computing Resources Provided by the Paderborn Center for Parallel Computing","_id":"52"}],"department":[{"_id":"34"},{"_id":"355"},{"_id":"26"}],"user_id":"5786","language":[{"iso":"eng"}]},{"year":"2021","citation":{"apa":"Webersen, M. (2021). <i>Zerstörungsfreie Charakterisierung der elastischen Materialeigenschaften thermoplastischer Polymerwerkstoffe mittels Ultraschall</i>. Universitätsbibliothek Paderborn. <a href=\"https://doi.org/10.17619/UNIPB/1-1088\">https://doi.org/10.17619/UNIPB/1-1088</a>","mla":"Webersen, Manuel. <i>Zerstörungsfreie Charakterisierung der elastischen Materialeigenschaften thermoplastischer Polymerwerkstoffe mittels Ultraschall</i>. Universitätsbibliothek Paderborn, 2021, doi:<a href=\"https://doi.org/10.17619/UNIPB/1-1088\">10.17619/UNIPB/1-1088</a>.","bibtex":"@book{Webersen_2021, title={Zerstörungsfreie Charakterisierung der elastischen Materialeigenschaften thermoplastischer Polymerwerkstoffe mittels Ultraschall}, DOI={<a href=\"https://doi.org/10.17619/UNIPB/1-1088\">10.17619/UNIPB/1-1088</a>}, publisher={Universitätsbibliothek Paderborn}, author={Webersen, Manuel}, year={2021} }","short":"M. Webersen, Zerstörungsfreie Charakterisierung der elastischen Materialeigenschaften thermoplastischer Polymerwerkstoffe mittels Ultraschall, Universitätsbibliothek Paderborn, 2021.","chicago":"Webersen, Manuel. <i>Zerstörungsfreie Charakterisierung der elastischen Materialeigenschaften thermoplastischer Polymerwerkstoffe mittels Ultraschall</i>. Universitätsbibliothek Paderborn, 2021. <a href=\"https://doi.org/10.17619/UNIPB/1-1088\">https://doi.org/10.17619/UNIPB/1-1088</a>.","ieee":"M. Webersen, <i>Zerstörungsfreie Charakterisierung der elastischen Materialeigenschaften thermoplastischer Polymerwerkstoffe mittels Ultraschall</i>. Universitätsbibliothek Paderborn, 2021.","ama":"Webersen M. <i>Zerstörungsfreie Charakterisierung der elastischen Materialeigenschaften thermoplastischer Polymerwerkstoffe mittels Ultraschall</i>. Universitätsbibliothek Paderborn; 2021. doi:<a href=\"https://doi.org/10.17619/UNIPB/1-1088\">10.17619/UNIPB/1-1088</a>"},"publication_status":"published","title":"Zerstörungsfreie Charakterisierung der elastischen Materialeigenschaften thermoplastischer Polymerwerkstoffe mittels Ultraschall","doi":"10.17619/UNIPB/1-1088","publisher":"Universitätsbibliothek Paderborn","date_updated":"2022-01-06T06:54:49Z","author":[{"first_name":"Manuel","full_name":"Webersen, Manuel","id":"11289","orcid":"0000-0001-6411-4232","last_name":"Webersen"}],"date_created":"2021-02-05T11:47:28Z","abstract":[{"text":"Die präzise Kenntnis der Eigenschaften verwendeter Materialien hat große Bedeutung für den Entwurf technischer Systeme aller Art, aber auch für die Überwachung solcher Systeme im Betrieb. Für verschiedene physikalische Eigenschaften, Betriebsbedingungen und Materialklassen werden daher geeignete messtechnische Verfahren zur Materialcharakterisierung benötigt. In der vorliegenden Arbeit wird ein Verfahren zur ultraschallbasierten Charakterisierung der mechanischen Eigenschaften von homogenen und faserverstärkten thermoplastischen Polymeren unter Berücksichtigung der Richtungsabhängigkeit vorgestellt. Plattenförmige Probekörper werden dazu mittels Laser-Pulsen hoher Energie breitbandig angeregt und die resultierenden akustischen Lamb-Wellen aufgezeichnet. Auf Basis der dispersiven Eigenschaften der detektierten Wellenleitermoden werden in einem inversen Verfahren die Parameter eines linear-elastischen Materialmodells identifiziert. Darüber hinaus wird ein Verfahren zur vollständigen Charakterisierung der Richtungsabhängigkeit in orthotropen Materialien wie Faserverbundwerkstoffen unter Verwendung eines zweidimensionalen Simulationsmodells vorgestellt. Das Messverfahren wird anhand einer Untersuchungsreihe an künstlich gealterten Polymer- und Faserverbundwerkstoffen verifiziert und die Übertragbarkeit der Ergebnisse auf den quasistatischen Fall betrachtet. Im Vergleich mit den Ergebnissen mechanischer Zugversuche werden die Voraussetzungen und Einschränkungen, insbesondere durch die Annahme eines ideal-elastischen Materialmodells, diskutiert.","lang":"ger"},{"lang":"eng","text":"Precise knowledge of material properties is a great concern in the design of technical systems, and in the monitoring of such systems during operation. Therefore, metrological processes are required for materials characterisation with respect to specific physical properties, operational conditions and classes of materials. In the work presented herein, a measurement procedure for the ultrasonic characterization of mechanical properties of homogeneous and fiber-reinforced thermoplastic polymer materials is presented, considering the different degrees of anisotropy. For this, acoustic Lamb waves are excited in a plate-shaped specimen using high-energy laser pulses, and then recorded.Based on the dispersive characteristics of the detected waveguide modes, an inverse procedure is applied to identify the parameters of a linear-elastic material model. Further, a procedure for completely characterising the orthotropy of materials like fiber-reinforced composites using a two-dimensional simulation model is presented. The measurement procedure is verified by examining artificially aged homogeneous polymers and composites, also considering the applicability of results to the quasistatic case. Comparing to the results of corresponding mechanical tensile tests, preconditions and limitations of the procedure are discussed, specifically regarding the assumption of an ideal-elastic material model."}],"status":"public","type":"dissertation","language":[{"iso":"ger"}],"_id":"21183","user_id":"11289","department":[{"_id":"49"}]},{"department":[{"_id":"101"}],"user_id":"32643","_id":"21195","language":[{"iso":"eng"}],"publication":"Cognitive Neurodynamics","type":"journal_article","status":"public","date_created":"2021-02-08T13:16:07Z","author":[{"full_name":"Goelz, Christian","last_name":"Goelz","first_name":"Christian"},{"first_name":"Karin","full_name":"Mora, Karin","last_name":"Mora"},{"first_name":"Julia Kristin","full_name":"Stroehlein, Julia Kristin","last_name":"Stroehlein"},{"full_name":"Haase, Franziska Katharina","last_name":"Haase","first_name":"Franziska Katharina"},{"full_name":"Dellnitz, Michael","last_name":"Dellnitz","first_name":"Michael"},{"last_name":"Reinsberger","full_name":"Reinsberger, Claus","first_name":"Claus"},{"last_name":"Vieluf","full_name":"Vieluf, Solveig","first_name":"Solveig"}],"date_updated":"2022-01-06T06:54:49Z","doi":"10.1007/s11571-020-09656-9","main_file_link":[{"url":"https://link.springer.com/content/pdf/10.1007/s11571-020-09656-9.pdf"}],"title":"Electrophysiological signatures of dedifferentiation differ between fit and less fit older adults","citation":{"apa":"Goelz, C., Mora, K., Stroehlein, J. K., Haase, F. K., Dellnitz, M., Reinsberger, C., &#38; Vieluf, S. (2021). Electrophysiological signatures of dedifferentiation differ between fit and less fit older adults. <i>Cognitive Neurodynamics</i>. <a href=\"https://doi.org/10.1007/s11571-020-09656-9\">https://doi.org/10.1007/s11571-020-09656-9</a>","short":"C. Goelz, K. Mora, J.K. Stroehlein, F.K. Haase, M. Dellnitz, C. Reinsberger, S. Vieluf, Cognitive Neurodynamics (2021).","bibtex":"@article{Goelz_Mora_Stroehlein_Haase_Dellnitz_Reinsberger_Vieluf_2021, title={Electrophysiological signatures of dedifferentiation differ between fit and less fit older adults}, DOI={<a href=\"https://doi.org/10.1007/s11571-020-09656-9\">10.1007/s11571-020-09656-9</a>}, journal={Cognitive Neurodynamics}, author={Goelz, Christian and Mora, Karin and Stroehlein, Julia Kristin and Haase, Franziska Katharina and Dellnitz, Michael and Reinsberger, Claus and Vieluf, Solveig}, year={2021} }","mla":"Goelz, Christian, et al. “Electrophysiological Signatures of Dedifferentiation Differ between Fit and Less Fit Older Adults.” <i>Cognitive Neurodynamics</i>, 2021, doi:<a href=\"https://doi.org/10.1007/s11571-020-09656-9\">10.1007/s11571-020-09656-9</a>.","ama":"Goelz C, Mora K, Stroehlein JK, et al. Electrophysiological signatures of dedifferentiation differ between fit and less fit older adults. <i>Cognitive Neurodynamics</i>. 2021. doi:<a href=\"https://doi.org/10.1007/s11571-020-09656-9\">10.1007/s11571-020-09656-9</a>","ieee":"C. Goelz <i>et al.</i>, “Electrophysiological signatures of dedifferentiation differ between fit and less fit older adults,” <i>Cognitive Neurodynamics</i>, 2021.","chicago":"Goelz, Christian, Karin Mora, Julia Kristin Stroehlein, Franziska Katharina Haase, Michael Dellnitz, Claus Reinsberger, and Solveig Vieluf. “Electrophysiological Signatures of Dedifferentiation Differ between Fit and Less Fit Older Adults.” <i>Cognitive Neurodynamics</i>, 2021. <a href=\"https://doi.org/10.1007/s11571-020-09656-9\">https://doi.org/10.1007/s11571-020-09656-9</a>."},"year":"2021"},{"date_updated":"2022-01-06T06:54:49Z","supervisor":[{"id":"20792","full_name":"Scheideler, Christian","last_name":"Scheideler","first_name":"Christian"}],"author":[{"full_name":"Mengshi, Ma","last_name":"Mengshi","first_name":"Ma"}],"date_created":"2021-02-09T07:09:22Z","title":"Self-stabilizing Arrow Protocol on Spanning Trees with a Low Diameter","year":"2021","citation":{"ieee":"M. Mengshi, <i>Self-stabilizing Arrow Protocol on Spanning Trees with a Low Diameter</i>. 2021.","chicago":"Mengshi, Ma. <i>Self-Stabilizing Arrow Protocol on Spanning Trees with a Low Diameter</i>, 2021.","ama":"Mengshi M. <i>Self-Stabilizing Arrow Protocol on Spanning Trees with a Low Diameter</i>.; 2021.","apa":"Mengshi, M. (2021). <i>Self-stabilizing Arrow Protocol on Spanning Trees with a Low Diameter</i>.","mla":"Mengshi, Ma. <i>Self-Stabilizing Arrow Protocol on Spanning Trees with a Low Diameter</i>. 2021.","short":"M. Mengshi, Self-Stabilizing Arrow Protocol on Spanning Trees with a Low Diameter, 2021.","bibtex":"@book{Mengshi_2021, title={Self-stabilizing Arrow Protocol on Spanning Trees with a Low Diameter}, author={Mengshi, Ma}, year={2021} }"},"_id":"21197","project":[{"_id":"1","name":"SFB 901"},{"_id":"2","name":"SFB 901 - Project Area A"},{"name":"SFB 901 - Project Area C","_id":"4"},{"_id":"5","name":"SFB 901 - Subproject A1"},{"_id":"13","name":"SFB 901 - Subproject C1"}],"department":[{"_id":"79"}],"user_id":"15504","language":[{"iso":"eng"}],"type":"bachelorsthesis","status":"public"},{"year":"2021","issue":"2","title":"Derivative-Free Multiobjective Trust Region Descent Method Using Radial  Basis Function Surrogate Models","date_created":"2021-03-01T10:46:48Z","abstract":[{"lang":"eng","text":"We present a flexible trust region descend algorithm for unconstrained and\r\nconvexly constrained multiobjective optimization problems. It is targeted at\r\nheterogeneous and expensive problems, i.e., problems that have at least one\r\nobjective function that is computationally expensive. The method is\r\nderivative-free in the sense that neither need derivative information be\r\navailable for the expensive objectives nor are gradients approximated using\r\nrepeated function evaluations as is the case in finite-difference methods.\r\nInstead, a multiobjective trust region approach is used that works similarly to\r\nits well-known scalar pendants. Local surrogate models constructed from\r\nevaluation data of the true objective functions are employed to compute\r\npossible descent directions. In contrast to existing multiobjective trust\r\nregion algorithms, these surrogates are not polynomial but carefully\r\nconstructed radial basis function networks. This has the important advantage\r\nthat the number of data points scales linearly with the parameter space\r\ndimension. The local models qualify as fully linear and the corresponding\r\ngeneral scalar framework is adapted for problems with multiple objectives.\r\nConvergence to Pareto critical points is proven and numerical examples\r\nillustrate our findings."}],"publication":"Mathematical and Computational Applications","language":[{"iso":"eng"}],"intvolume":"        26","citation":{"mla":"Berkemeier, Manuel Bastian, and Sebastian Peitz. “Derivative-Free Multiobjective Trust Region Descent Method Using Radial  Basis Function Surrogate Models.” <i>Mathematical and Computational Applications</i>, vol. 26, no. 2, 31, 2021, doi:<a href=\"https://doi.org/10.3390/mca26020031\">10.3390/mca26020031</a>.","short":"M.B. Berkemeier, S. Peitz, Mathematical and Computational Applications 26 (2021).","bibtex":"@article{Berkemeier_Peitz_2021, title={Derivative-Free Multiobjective Trust Region Descent Method Using Radial  Basis Function Surrogate Models}, volume={26}, DOI={<a href=\"https://doi.org/10.3390/mca26020031\">10.3390/mca26020031</a>}, number={231}, journal={Mathematical and Computational Applications}, author={Berkemeier, Manuel Bastian and Peitz, Sebastian}, year={2021} }","apa":"Berkemeier, M. B., &#38; Peitz, S. (2021). Derivative-Free Multiobjective Trust Region Descent Method Using Radial  Basis Function Surrogate Models. <i>Mathematical and Computational Applications</i>, <i>26</i>(2). <a href=\"https://doi.org/10.3390/mca26020031\">https://doi.org/10.3390/mca26020031</a>","chicago":"Berkemeier, Manuel Bastian, and Sebastian Peitz. “Derivative-Free Multiobjective Trust Region Descent Method Using Radial  Basis Function Surrogate Models.” <i>Mathematical and Computational Applications</i> 26, no. 2 (2021). <a href=\"https://doi.org/10.3390/mca26020031\">https://doi.org/10.3390/mca26020031</a>.","ieee":"M. B. Berkemeier and S. Peitz, “Derivative-Free Multiobjective Trust Region Descent Method Using Radial  Basis Function Surrogate Models,” <i>Mathematical and Computational Applications</i>, vol. 26, no. 2, 2021.","ama":"Berkemeier MB, Peitz S. Derivative-Free Multiobjective Trust Region Descent Method Using Radial  Basis Function Surrogate Models. <i>Mathematical and Computational Applications</i>. 2021;26(2). doi:<a href=\"https://doi.org/10.3390/mca26020031\">10.3390/mca26020031</a>"},"publication_identifier":{"eissn":["2297-8747"]},"publication_status":"published","doi":"10.3390/mca26020031","main_file_link":[{"open_access":"1","url":"https://www.mdpi.com/2297-8747/26/2/31/pdf"}],"oa":"1","date_updated":"2022-01-06T06:54:55Z","volume":26,"author":[{"full_name":"Berkemeier, Manuel Bastian","id":"51701","last_name":"Berkemeier","first_name":"Manuel Bastian"},{"orcid":"0000-0002-3389-793X","last_name":"Peitz","full_name":"Peitz, Sebastian","id":"47427","first_name":"Sebastian"}],"status":"public","type":"journal_article","article_number":"31","_id":"21337","department":[{"_id":"101"},{"_id":"655"}],"user_id":"47427"}]