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New York, NY, United States: Association for Computing Machinery (ACM), 2021. <a href=\"https://doi.org/10.1145/3449726.3463159\">https://doi.org/10.1145/3449726.3463159</a>."},"page":"1639–1647","year":"2021","place":"New York, NY, United States","publication_status":"published","publication_identifier":{"isbn":["978-1-4503-8351-6"]},"doi":"10.1145/3449726.3463159","conference":{"location":"Lille, France","end_date":"2021-07-14","start_date":"2021-07-10","name":"International Workshop on Learning Classifier Systems (IWLCS 2021)"},"title":"An Experimental Comparison of Explore/Exploit Strategies for the Learning Classifier System XCS","author":[{"last_name":"Hansmeier","orcid":"0000-0003-1377-3339","id":"49992","full_name":"Hansmeier, Tim","first_name":"Tim"},{"last_name":"Platzner","full_name":"Platzner, Marco","id":"398","first_name":"Marco"}],"date_created":"2021-04-28T09:08:17Z","publisher":"Association for Computing Machinery (ACM)","date_updated":"2022-09-02T09:42:38Z"},{"title":"Full Version -- Server Cloud Scheduling","date_updated":"2022-09-27T15:03:19Z","author":[{"first_name":"Marten","last_name":"Maack","full_name":"Maack, Marten","id":"88252"},{"first_name":"Friedhelm","full_name":"Meyer auf der Heide, Friedhelm","id":"15523","last_name":"Meyer auf der Heide"},{"id":"44428","full_name":"Pukrop, Simon","last_name":"Pukrop","first_name":"Simon"}],"date_created":"2021-11-24T13:23:58Z","year":"2021","citation":{"short":"M. Maack, F. Meyer auf der Heide, S. Pukrop, ArXiv:2108.02109 (2021).","mla":"Maack, Marten, et al. “Full Version -- Server Cloud Scheduling.” <i>ArXiv:2108.02109</i>, 2021.","bibtex":"@article{Maack_Meyer auf der Heide_Pukrop_2021, title={Full Version -- Server Cloud Scheduling}, journal={arXiv:2108.02109}, author={Maack, Marten and Meyer auf der Heide, Friedhelm and Pukrop, Simon}, year={2021} }","apa":"Maack, M., Meyer auf der Heide, F., &#38; Pukrop, S. (2021). Full Version -- Server Cloud Scheduling. In <i>arXiv:2108.02109</i>.","ama":"Maack M, Meyer auf der Heide F, Pukrop S. Full Version -- Server Cloud Scheduling. <i>arXiv:210802109</i>. Published online 2021.","chicago":"Maack, Marten, Friedhelm Meyer auf der Heide, and Simon Pukrop. “Full Version -- Server Cloud Scheduling.” <i>ArXiv:2108.02109</i>, 2021.","ieee":"M. Maack, F. Meyer auf der Heide, and S. Pukrop, “Full Version -- Server Cloud Scheduling,” <i>arXiv:2108.02109</i>. 2021."},"language":[{"iso":"eng"}],"_id":"27778","department":[{"_id":"63"},{"_id":"26"}],"user_id":"44428","abstract":[{"lang":"eng","text":"Consider a set of jobs connected to a directed acyclic task graph with a\r\nfixed source and sink. The edges of this graph model precedence constraints and\r\nthe jobs have to be scheduled with respect to those. We introduce the Server\r\nCloud Scheduling problem, in which the jobs have to be processed either on a\r\nsingle local machine or on one of many cloud machines. Both the source and the\r\nsink have to be scheduled on the local machine. For each job, processing times\r\nboth on the server and in the cloud are given. Furthermore, for each edge in\r\nthe task graph, a communication delay is included in the input and has to be\r\ntaken into account if one of the two jobs is scheduled on the server, the other\r\nin the cloud. The server can process jobs sequentially, whereas the cloud can\r\nserve as many as needed in parallel, but induces costs. We consider both\r\nmakespan and cost minimization. The main results are an FPTAS with respect for\r\nthe makespan objective for a fairly general case and strong hardness for the\r\ncase with unit processing times and delays."}],"status":"public","publication":"arXiv:2108.02109","type":"preprint"},{"publication_status":"published","year":"2021","citation":{"chicago":"Wiecher, Carsten, Jannik Fischbach, Joel Greenyer, Andreas Vogelsang, Carsten Wolff, and Roman Dumitrescu. “Integrated and Iterative Requirements Analysis and Test Specification: A Case Study at Kostal.” <i>ArXiv Preprint</i>, 2021.","ieee":"C. Wiecher, J. Fischbach, J. Greenyer, A. Vogelsang, C. Wolff, and R. Dumitrescu, “Integrated and Iterative Requirements Analysis and Test Specification: A Case Study at Kostal,” <i>arXiv preprint</i>, 2021.","ama":"Wiecher C, Fischbach J, Greenyer J, Vogelsang A, Wolff C, Dumitrescu R. Integrated and Iterative Requirements Analysis and Test Specification: A Case Study at Kostal. <i>arXiv preprint</i>. 2021.","apa":"Wiecher, C., Fischbach, J., Greenyer, J., Vogelsang, A., Wolff, C., &#38; Dumitrescu, R. (2021). Integrated and Iterative Requirements Analysis and Test Specification: A Case Study at Kostal. <i>ArXiv Preprint</i>.","bibtex":"@article{Wiecher_Fischbach_Greenyer_Vogelsang_Wolff_Dumitrescu_2021, title={Integrated and Iterative Requirements Analysis and Test Specification: A Case Study at Kostal}, journal={arXiv preprint}, author={Wiecher, Carsten and Fischbach, Jannik and Greenyer, Joel and Vogelsang, Andreas and Wolff, Carsten and Dumitrescu, Roman}, year={2021} }","short":"C. Wiecher, J. Fischbach, J. Greenyer, A. Vogelsang, C. Wolff, R. Dumitrescu, ArXiv Preprint (2021).","mla":"Wiecher, Carsten, et al. “Integrated and Iterative Requirements Analysis and Test Specification: A Case Study at Kostal.” <i>ArXiv Preprint</i>, 2021."},"date_updated":"2022-10-13T11:01:39Z","author":[{"last_name":"Wiecher","full_name":"Wiecher, Carsten","first_name":"Carsten"},{"full_name":"Fischbach, Jannik","last_name":"Fischbach","first_name":"Jannik"},{"last_name":"Greenyer","full_name":"Greenyer, Joel","first_name":"Joel"},{"first_name":"Andreas","last_name":"Vogelsang","full_name":"Vogelsang, Andreas"},{"last_name":"Wolff","full_name":"Wolff, Carsten","first_name":"Carsten"},{"first_name":"Roman","id":"16190","full_name":"Dumitrescu, Roman","last_name":"Dumitrescu"}],"date_created":"2021-11-02T14:54:31Z","title":"Integrated and Iterative Requirements Analysis and Test Specification: A Case Study at Kostal","type":"newspaper_article","publication":"arXiv preprint","status":"public","publication_date":"2021-07-12","_id":"27058","user_id":"15782","department":[{"_id":"563"}],"language":[{"iso":"eng"}]},{"status":"public","type":"book_chapter","publication":"Intelligent Data Engineering and Automated Learning – IDEAL 2021","language":[{"iso":"eng"}],"_id":"29292","user_id":"11871","department":[{"_id":"574"}],"place":"Cham","year":"2021","citation":{"ieee":"R. Feldhans <i>et al.</i>, “Drift Detection in Text Data with Document Embeddings,” in <i>Intelligent Data Engineering and Automated Learning – IDEAL 2021</i>, Cham: Springer International Publishing, 2021.","chicago":"Feldhans, Robert, Adrian Wilke, Stefan Heindorf, Mohammad Hossein Shaker, Barbara Hammer, Axel-Cyrille Ngonga Ngomo, and Eyke Hüllermeier. “Drift Detection in Text Data with Document Embeddings.” In <i>Intelligent Data Engineering and Automated Learning – IDEAL 2021</i>. Cham: Springer International Publishing, 2021. <a href=\"https://doi.org/10.1007/978-3-030-91608-4_11\">https://doi.org/10.1007/978-3-030-91608-4_11</a>.","ama":"Feldhans R, Wilke A, Heindorf S, et al. Drift Detection in Text Data with Document Embeddings. In: <i>Intelligent Data Engineering and Automated Learning – IDEAL 2021</i>. Springer International Publishing; 2021. doi:<a href=\"https://doi.org/10.1007/978-3-030-91608-4_11\">10.1007/978-3-030-91608-4_11</a>","apa":"Feldhans, R., Wilke, A., Heindorf, S., Shaker, M. H., Hammer, B., Ngonga Ngomo, A.-C., &#38; Hüllermeier, E. (2021). Drift Detection in Text Data with Document Embeddings. In <i>Intelligent Data Engineering and Automated Learning – IDEAL 2021</i>. Springer International Publishing. <a href=\"https://doi.org/10.1007/978-3-030-91608-4_11\">https://doi.org/10.1007/978-3-030-91608-4_11</a>","bibtex":"@inbook{Feldhans_Wilke_Heindorf_Shaker_Hammer_Ngonga Ngomo_Hüllermeier_2021, place={Cham}, title={Drift Detection in Text Data with Document Embeddings}, DOI={<a href=\"https://doi.org/10.1007/978-3-030-91608-4_11\">10.1007/978-3-030-91608-4_11</a>}, booktitle={Intelligent Data Engineering and Automated Learning – IDEAL 2021}, publisher={Springer International Publishing}, author={Feldhans, Robert and Wilke, Adrian and Heindorf, Stefan and Shaker, Mohammad Hossein and Hammer, Barbara and Ngonga Ngomo, Axel-Cyrille and Hüllermeier, Eyke}, year={2021} }","mla":"Feldhans, Robert, et al. “Drift Detection in Text Data with Document Embeddings.” <i>Intelligent Data Engineering and Automated Learning – IDEAL 2021</i>, Springer International Publishing, 2021, doi:<a href=\"https://doi.org/10.1007/978-3-030-91608-4_11\">10.1007/978-3-030-91608-4_11</a>.","short":"R. Feldhans, A. Wilke, S. Heindorf, M.H. Shaker, B. Hammer, A.-C. Ngonga Ngomo, E. Hüllermeier, in: Intelligent Data Engineering and Automated Learning – IDEAL 2021, Springer International Publishing, Cham, 2021."},"publication_status":"published","publication_identifier":{"isbn":["9783030916077","9783030916084"],"issn":["0302-9743","1611-3349"]},"related_material":{"link":[{"relation":"confirmation","url":"https://link.springer.com/chapter/10.1007/978-3-030-91608-4_11"}]},"title":"Drift Detection in Text Data with Document Embeddings","main_file_link":[{"url":"https://papers.dice-research.org/2021/IDEAL2021_DriftDetectionEmbeddings/Drift-Detection-in-Text-Data-with-Document-Embeddings-public.pdf","open_access":"1"}],"doi":"10.1007/978-3-030-91608-4_11","date_updated":"2022-10-15T19:54:20Z","oa":"1","publisher":"Springer International Publishing","author":[{"first_name":"Robert","full_name":"Feldhans, Robert","last_name":"Feldhans"},{"orcid":"0000-0002-6575-807X","last_name":"Wilke","full_name":"Wilke, Adrian","id":"9101","first_name":"Adrian"},{"first_name":"Stefan","last_name":"Heindorf","orcid":"0000-0002-4525-6865","id":"11871","full_name":"Heindorf, Stefan"},{"first_name":"Mohammad Hossein","last_name":"Shaker","full_name":"Shaker, Mohammad Hossein"},{"first_name":"Barbara","last_name":"Hammer","full_name":"Hammer, Barbara"},{"first_name":"Axel-Cyrille","last_name":"Ngonga Ngomo","full_name":"Ngonga Ngomo, Axel-Cyrille","id":"65716"},{"last_name":"Hüllermeier","full_name":"Hüllermeier, Eyke","id":"48129","first_name":"Eyke"}],"date_created":"2022-01-12T10:27:23Z"},{"year":"2021","citation":{"apa":"Demir, C., Moussallem, D., Heindorf, S., &#38; Ngonga Ngomo, A.-C. (2021). Convolutional Hypercomplex Embeddings for Link Prediction. <i>The 13th Asian Conference on Machine Learning, ACML 2021</i>.","mla":"Demir, Caglar, et al. “Convolutional Hypercomplex Embeddings for Link Prediction.” <i>The 13th Asian Conference on Machine Learning, ACML 2021</i>, 2021.","bibtex":"@inproceedings{Demir_Moussallem_Heindorf_Ngonga Ngomo_2021, title={Convolutional Hypercomplex Embeddings for Link Prediction}, booktitle={The 13th Asian Conference on Machine Learning, ACML 2021}, author={Demir, Caglar and Moussallem, Diego and Heindorf, Stefan and Ngonga Ngomo, Axel-Cyrille}, year={2021} }","short":"C. Demir, D. Moussallem, S. Heindorf, A.-C. Ngonga Ngomo, in: The 13th Asian Conference on Machine Learning, ACML 2021, 2021.","chicago":"Demir, Caglar, Diego Moussallem, Stefan Heindorf, and Axel-Cyrille Ngonga Ngomo. “Convolutional Hypercomplex Embeddings for Link Prediction.” In <i>The 13th Asian Conference on Machine Learning, ACML 2021</i>, 2021.","ieee":"C. Demir, D. Moussallem, S. Heindorf, and A.-C. Ngonga Ngomo, “Convolutional Hypercomplex Embeddings for Link Prediction,” 2021.","ama":"Demir C, Moussallem D, Heindorf S, Ngonga Ngomo A-C. Convolutional Hypercomplex Embeddings for Link Prediction. In: <i>The 13th Asian Conference on Machine Learning, ACML 2021</i>. ; 2021."},"title":"Convolutional Hypercomplex Embeddings for Link Prediction","main_file_link":[{"open_access":"1","url":"https://papers.dice-research.org/2021/ACML2021_HyperConv/public.pdf"}],"date_updated":"2022-10-17T15:06:40Z","oa":"1","date_created":"2022-01-12T10:21:10Z","author":[{"first_name":"Caglar","id":"43817","full_name":"Demir, Caglar","last_name":"Demir"},{"last_name":"Moussallem","full_name":"Moussallem, Diego","id":"71635","first_name":"Diego"},{"first_name":"Stefan","id":"11871","full_name":"Heindorf, Stefan","last_name":"Heindorf","orcid":"0000-0002-4525-6865"},{"full_name":"Ngonga Ngomo, Axel-Cyrille","id":"65716","last_name":"Ngonga Ngomo","first_name":"Axel-Cyrille"}],"abstract":[{"lang":"eng","text":"Knowledge graph embedding research has mainly focused on the two smallest\r\nnormed division algebras, $\\mathbb{R}$ and $\\mathbb{C}$. Recent results suggest\r\nthat trilinear products of quaternion-valued embeddings can be a more effective\r\nmeans to tackle link prediction. In addition, models based on convolutions on\r\nreal-valued embeddings often yield state-of-the-art results for link\r\nprediction. In this paper, we investigate a composition of convolution\r\noperations with hypercomplex multiplications. We propose the four approaches\r\nQMult, OMult, ConvQ and ConvO to tackle the link prediction problem. QMult and\r\nOMult can be considered as quaternion and octonion extensions of previous\r\nstate-of-the-art approaches, including DistMult and ComplEx. ConvQ and ConvO\r\nbuild upon QMult and OMult by including convolution operations in a way\r\ninspired by the residual learning framework. We evaluated our approaches on\r\nseven link prediction datasets including WN18RR, FB15K-237 and YAGO3-10.\r\nExperimental results suggest that the benefits of learning hypercomplex-valued\r\nvector representations become more apparent as the size and complexity of the\r\nknowledge graph grows. ConvO outperforms state-of-the-art approaches on\r\nFB15K-237 in MRR, Hit@1 and Hit@3, while QMult, OMult, ConvQ and ConvO\r\noutperform state-of-the-approaches on YAGO3-10 in all metrics. Results also\r\nsuggest that link prediction performances can be further improved via\r\nprediction averaging. To foster reproducible research, we provide an\r\nopen-source implementation of approaches, including training and evaluation\r\nscripts as well as pretrained models."}],"status":"public","type":"conference","publication":"The 13th Asian Conference on Machine Learning, ACML 2021","language":[{"iso":"eng"}],"_id":"29287","external_id":{"arxiv":["2106.15230"]},"user_id":"11871","department":[{"_id":"574"}]},{"project":[{"_id":"52","name":"PC2: Computing Resources Provided by the Paderborn Center for Parallel Computing"}],"_id":"29294","user_id":"11871","department":[{"_id":"66"},{"_id":"574"}],"language":[{"iso":"eng"}],"type":"conference","publication":"2021 IEEE Winter Conference on Applications of Computer Vision (WACV)","status":"public","publisher":"IEEE","oa":"1","date_updated":"2022-10-17T15:07:38Z","date_created":"2022-01-12T10:31:42Z","author":[{"id":"27340","full_name":"Nickchen, Tobias","orcid":"0000-0001-8958-9330","last_name":"Nickchen","first_name":"Tobias"},{"first_name":"Stefan","orcid":"0000-0002-4525-6865","last_name":"Heindorf","id":"11871","full_name":"Heindorf, Stefan"},{"last_name":"Engels","full_name":"Engels, Gregor","id":"107","first_name":"Gregor"}],"title":"Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts","main_file_link":[{"url":"https://openaccess.thecvf.com/content/WACV2021/papers/Nickchen_Generating_Physically_Sound_Training_Data_for_Image_Recognition_of_Additively_WACV_2021_paper.pdf","open_access":"1"}],"doi":"10.1109/wacv48630.2021.00204","publication_status":"published","year":"2021","citation":{"ieee":"T. Nickchen, S. Heindorf, and G. Engels, “Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts,” 2021, doi: <a href=\"https://doi.org/10.1109/wacv48630.2021.00204\">10.1109/wacv48630.2021.00204</a>.","chicago":"Nickchen, Tobias, Stefan Heindorf, and Gregor Engels. “Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts.” In <i>2021 IEEE Winter Conference on Applications of Computer Vision (WACV)</i>. IEEE, 2021. <a href=\"https://doi.org/10.1109/wacv48630.2021.00204\">https://doi.org/10.1109/wacv48630.2021.00204</a>.","ama":"Nickchen T, Heindorf S, Engels G. Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts. In: <i>2021 IEEE Winter Conference on Applications of Computer Vision (WACV)</i>. IEEE; 2021. doi:<a href=\"https://doi.org/10.1109/wacv48630.2021.00204\">10.1109/wacv48630.2021.00204</a>","mla":"Nickchen, Tobias, et al. “Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts.” <i>2021 IEEE Winter Conference on Applications of Computer Vision (WACV)</i>, IEEE, 2021, doi:<a href=\"https://doi.org/10.1109/wacv48630.2021.00204\">10.1109/wacv48630.2021.00204</a>.","short":"T. Nickchen, S. Heindorf, G. Engels, in: 2021 IEEE Winter Conference on Applications of Computer Vision (WACV), IEEE, 2021.","bibtex":"@inproceedings{Nickchen_Heindorf_Engels_2021, title={Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts}, DOI={<a href=\"https://doi.org/10.1109/wacv48630.2021.00204\">10.1109/wacv48630.2021.00204</a>}, booktitle={2021 IEEE Winter Conference on Applications of Computer Vision (WACV)}, publisher={IEEE}, author={Nickchen, Tobias and Heindorf, Stefan and Engels, Gregor}, year={2021} }","apa":"Nickchen, T., Heindorf, S., &#38; Engels, G. (2021). Generating Physically Sound Training Data for Image Recognition of Additively Manufactured Parts. <i>2021 IEEE Winter Conference on Applications of Computer Vision (WACV)</i>. <a href=\"https://doi.org/10.1109/wacv48630.2021.00204\">https://doi.org/10.1109/wacv48630.2021.00204</a>"}},{"language":[{"iso":"eng"}],"user_id":"15249","department":[{"_id":"76"},{"_id":"662"}],"_id":"26407","status":"public","type":"conference","publication":"2021 IEEE 21st International Working Conference on Source Code Analysis and Manipulation (SCAM)","title":"SecuCheck: Engineering configurable taint analysis for software developers","date_created":"2021-10-18T12:53:15Z","author":[{"first_name":"Goran","id":"41936","full_name":"Piskachev, Goran","orcid":"0000-0003-4424-5838","last_name":"Piskachev"},{"last_name":"Krishnamurthy","full_name":"Krishnamurthy, Ranjith","first_name":"Ranjith"},{"first_name":"Eric","id":"59256","full_name":"Bodden, Eric","orcid":"0000-0003-3470-3647","last_name":"Bodden"}],"date_updated":"2022-10-20T12:44:31Z","citation":{"apa":"Piskachev, G., Krishnamurthy, R., &#38; Bodden, E. (2021). SecuCheck: Engineering configurable taint analysis for software developers. <i>2021 IEEE 21st International Working Conference on Source Code Analysis and Manipulation (SCAM)</i>.","short":"G. Piskachev, R. Krishnamurthy, E. Bodden, in: 2021 IEEE 21st International Working Conference on Source Code Analysis and Manipulation (SCAM), 2021.","mla":"Piskachev, Goran, et al. “SecuCheck: Engineering Configurable Taint Analysis for Software Developers.” <i>2021 IEEE 21st International Working Conference on Source Code Analysis and Manipulation (SCAM)</i>, 2021.","bibtex":"@inproceedings{Piskachev_Krishnamurthy_Bodden_2021, title={SecuCheck: Engineering configurable taint analysis for software developers}, booktitle={2021 IEEE 21st International Working Conference on Source Code Analysis and Manipulation (SCAM)}, author={Piskachev, Goran and Krishnamurthy, Ranjith and Bodden, Eric}, year={2021} }","ama":"Piskachev G, Krishnamurthy R, Bodden E. SecuCheck: Engineering configurable taint analysis for software developers. In: <i>2021 IEEE 21st International Working Conference on Source Code Analysis and Manipulation (SCAM)</i>. ; 2021.","chicago":"Piskachev, Goran, Ranjith Krishnamurthy, and Eric Bodden. “SecuCheck: Engineering Configurable Taint Analysis for Software Developers.” In <i>2021 IEEE 21st International Working Conference on Source Code Analysis and Manipulation (SCAM)</i>, 2021.","ieee":"G. Piskachev, R. Krishnamurthy, and E. Bodden, “SecuCheck: Engineering configurable taint analysis for software developers,” 2021."},"year":"2021"},{"citation":{"mla":"Luo, Linghui, et al. “IDE Support for Cloud-Based Static Analyses.” <i>Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering</i>, 2021.","bibtex":"@inproceedings{Luo_Schäf_Sanchez_Bodden_2021, title={IDE Support for Cloud-Based Static Analyses}, booktitle={Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering}, author={Luo, Linghui and Schäf, Martin and Sanchez, Daniel and Bodden, Eric}, year={2021} }","short":"L. Luo, M. Schäf, D. Sanchez, E. Bodden, in: Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2021.","apa":"Luo, L., Schäf, M., Sanchez, D., &#38; Bodden, E. (2021). IDE Support for Cloud-Based Static Analyses. <i>Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering</i>.","chicago":"Luo, Linghui, Martin Schäf, Daniel Sanchez, and Eric Bodden. “IDE Support for Cloud-Based Static Analyses.” In <i>Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering</i>, 2021.","ieee":"L. Luo, M. Schäf, D. Sanchez, and E. Bodden, “IDE Support for Cloud-Based Static Analyses,” 2021.","ama":"Luo L, Schäf M, Sanchez D, Bodden E. IDE Support for Cloud-Based Static Analyses. In: <i>Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering</i>. ; 2021."},"year":"2021","title":"IDE Support for Cloud-Based Static Analyses","author":[{"first_name":"Linghui","last_name":"Luo","full_name":"Luo, Linghui"},{"first_name":"Martin","last_name":"Schäf","full_name":"Schäf, Martin"},{"full_name":"Sanchez, Daniel","last_name":"Sanchez","first_name":"Daniel"},{"full_name":"Bodden, Eric","id":"59256","last_name":"Bodden","orcid":"0000-0003-3470-3647","first_name":"Eric"}],"date_created":"2021-06-17T10:18:05Z","date_updated":"2022-10-20T13:11:45Z","status":"public","publication":"Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering","type":"conference","language":[{"iso":"eng"}],"department":[{"_id":"76"}],"user_id":"15249","_id":"22463"},{"title":"SootFX: A Static Code Feature Extraction Tool for Java and Android","date_updated":"2022-10-20T13:09:23Z","author":[{"orcid":"https://orcid.org/0000-0001-9266-2084","last_name":"Karakaya","full_name":"Karakaya, Kadiray","id":"70410","first_name":"Kadiray"},{"id":"59256","full_name":"Bodden, Eric","orcid":"0000-0003-3470-3647","last_name":"Bodden","first_name":"Eric"}],"date_created":"2022-10-20T13:09:08Z","year":"2021","citation":{"apa":"Karakaya, K., &#38; Bodden, E. (2021). SootFX: A Static Code Feature Extraction Tool for Java and Android. <i>2021 IEEE 21st International Working Conference on Source Code Analysis and Manipulation (SCAM)</i>, 181–186.","short":"K. Karakaya, E. Bodden, in: 2021 IEEE 21st International Working Conference on Source Code Analysis and Manipulation (SCAM), 2021, pp. 181–186.","mla":"Karakaya, Kadiray, and Eric Bodden. “SootFX: A Static Code Feature Extraction Tool for Java and Android.” <i>2021 IEEE 21st International Working Conference on Source Code Analysis and Manipulation (SCAM)</i>, 2021, pp. 181–186.","bibtex":"@inproceedings{Karakaya_Bodden_2021, title={SootFX: A Static Code Feature Extraction Tool for Java and Android}, booktitle={2021 IEEE 21st International Working Conference on Source Code Analysis and Manipulation (SCAM)}, author={Karakaya, Kadiray and Bodden, Eric}, year={2021}, pages={181–186} }","ieee":"K. Karakaya and E. Bodden, “SootFX: A Static Code Feature Extraction Tool for Java and Android,” in <i>2021 IEEE 21st International Working Conference on Source Code Analysis and Manipulation (SCAM)</i>, 2021, pp. 181–186.","chicago":"Karakaya, Kadiray, and Eric Bodden. “SootFX: A Static Code Feature Extraction Tool for Java and Android.” In <i>2021 IEEE 21st International Working Conference on Source Code Analysis and Manipulation (SCAM)</i>, 181–186, 2021.","ama":"Karakaya K, Bodden E. SootFX: A Static Code Feature Extraction Tool for Java and Android. In: <i>2021 IEEE 21st International Working Conference on Source Code Analysis and Manipulation (SCAM)</i>. ; 2021:181–186."},"page":"181–186","language":[{"iso":"eng"}],"_id":"33840","user_id":"15249","department":[{"_id":"76"}],"status":"public","type":"conference","publication":"2021 IEEE 21st International Working Conference on Source Code Analysis and Manipulation (SCAM)"},{"language":[{"iso":"eng"}],"_id":"32401","department":[{"_id":"64"}],"user_id":"47434","status":"public","type":"bachelorsthesis","title":"Lattice reductions and their applications to cryptographic systems","date_updated":"2023-01-10T10:49:33Z","date_created":"2022-07-20T11:40:28Z","author":[{"full_name":"Siemer, Jan Niklas","last_name":"Siemer","first_name":"Jan Niklas"}],"supervisor":[{"first_name":"Johannes","last_name":"Blömer","full_name":"Blömer, Johannes","id":"23"}],"year":"2021","citation":{"ieee":"J. N. Siemer, <i>Lattice reductions and their applications to cryptographic systems</i>. 2021.","chicago":"Siemer, Jan Niklas. <i>Lattice Reductions and Their Applications to Cryptographic Systems</i>, 2021.","ama":"Siemer JN. <i>Lattice Reductions and Their Applications to Cryptographic Systems</i>.; 2021.","short":"J.N. Siemer, Lattice Reductions and Their Applications to Cryptographic Systems, 2021.","mla":"Siemer, Jan Niklas. <i>Lattice Reductions and Their Applications to Cryptographic Systems</i>. 2021.","bibtex":"@book{Siemer_2021, title={Lattice reductions and their applications to cryptographic systems}, author={Siemer, Jan Niklas}, year={2021} }","apa":"Siemer, J. N. (2021). <i>Lattice reductions and their applications to cryptographic systems</i>."}},{"date_updated":"2023-01-10T11:54:39Z","author":[{"full_name":"Anonymous, Anonymous","last_name":"Anonymous","first_name":"Anonymous"}],"supervisor":[{"first_name":"Johannes","id":"23","full_name":"Blömer, Johannes","last_name":"Blömer"}],"date_created":"2022-07-20T11:37:41Z","title":"Performance Analysis of FHE Libraries","year":"2021","citation":{"apa":"Anonymous, A. (2021). <i>Performance Analysis of FHE Libraries</i>.","bibtex":"@book{Anonymous_2021, title={Performance Analysis of FHE Libraries}, author={Anonymous, Anonymous}, year={2021} }","short":"A. Anonymous, Performance Analysis of FHE Libraries, 2021.","mla":"Anonymous, Anonymous. <i>Performance Analysis of FHE Libraries</i>. 2021.","ama":"Anonymous A. <i>Performance Analysis of FHE Libraries</i>.; 2021.","ieee":"A. Anonymous, <i>Performance Analysis of FHE Libraries</i>. 2021.","chicago":"Anonymous, Anonymous. <i>Performance Analysis of FHE Libraries</i>, 2021."},"_id":"32400","user_id":"47434","department":[{"_id":"64"}],"language":[{"iso":"eng"}],"type":"mastersthesis","status":"public"},{"year":"2021","citation":{"chicago":"Schneider, Stefan Balthasar. <i>Conventional and Machine Learning Approaches for Network and Service Coordination</i>, 2021.","ieee":"S. B. Schneider, <i>Conventional and Machine Learning Approaches for Network and Service Coordination</i>. 2021.","ama":"Schneider SB. <i>Conventional and Machine Learning Approaches for Network and Service Coordination</i>.; 2021.","bibtex":"@book{Schneider_2021, title={Conventional and Machine Learning Approaches for Network and Service Coordination}, author={Schneider, Stefan Balthasar}, year={2021} }","short":"S.B. Schneider, Conventional and Machine Learning Approaches for Network and Service Coordination, 2021.","mla":"Schneider, Stefan Balthasar. <i>Conventional and Machine Learning Approaches for Network and Service Coordination</i>. 2021.","apa":"Schneider, S. B. (2021). <i>Conventional and Machine Learning Approaches for Network and Service Coordination</i>."},"has_accepted_license":"1","title":"Conventional and Machine Learning Approaches for Network and Service Coordination","date_updated":"2023-01-10T15:09:05Z","oa":"1","date_created":"2023-01-10T15:08:50Z","author":[{"first_name":"Stefan Balthasar","full_name":"Schneider, Stefan Balthasar","id":"35343","last_name":"Schneider","orcid":"0000-0001-8210-4011"}],"abstract":[{"text":"Network and service coordination is important to provide modern services consisting of multiple interconnected components, e.g., in 5G, network function virtualization (NFV), or cloud and edge computing. In this paper, I outline my dissertation research, which proposes six approaches to automate such network and service coordination. All approaches dynamically react to the current demand and optimize coordination for high service quality and low costs. The approaches range from centralized to distributed methods and from conventional heuristic algorithms and mixed-integer linear programs to machine learning approaches using supervised and reinforcement learning. I briefly discuss their main ideas and advantages over other state-of-the-art approaches and compare strengths and weaknesses.","lang":"eng"}],"file":[{"relation":"main_file","content_type":"application/pdf","file_id":"35890","file_name":"main.pdf","access_level":"open_access","file_size":133340,"creator":"stschn","date_created":"2023-01-10T15:07:03Z","date_updated":"2023-01-10T15:07:03Z"}],"status":"public","type":"working_paper","ddc":["004"],"keyword":["nfv","coordination","machine learning","reinforcement learning","phd","digest"],"file_date_updated":"2023-01-10T15:07:03Z","language":[{"iso":"eng"}],"project":[{"name":"SFB 901: SFB 901","_id":"1"},{"_id":"4","name":"SFB 901 - C: SFB 901 - Project Area C"},{"_id":"16","name":"SFB 901 - C4: SFB 901 - Subproject C4"}],"_id":"35889","user_id":"35343","department":[{"_id":"75"}]},{"date_updated":"2023-10-16T12:58:42Z","volume":136,"author":[{"first_name":"Christian","full_name":"Grimme, Christian","last_name":"Grimme"},{"full_name":"Kerschke, Pascal","last_name":"Kerschke","first_name":"Pascal"},{"full_name":"Aspar, Pelin","last_name":"Aspar","first_name":"Pelin"},{"last_name":"Trautmann","orcid":"0000-0002-9788-8282","id":"100740","full_name":"Trautmann, Heike","first_name":"Heike"},{"last_name":"Preuss","full_name":"Preuss, Mike","first_name":"Mike"},{"first_name":"André H.","full_name":"Deutz, André H.","last_name":"Deutz"},{"first_name":"Hao","last_name":"Wang","full_name":"Wang, Hao"},{"full_name":"Emmerich, Michael","last_name":"Emmerich","first_name":"Michael"}],"date_created":"2023-08-04T07:28:34Z","title":"Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization","doi":"https://doi.org/10.1016/j.cor.2021.105489","publication_identifier":{"issn":["0305-0548"]},"year":"2021","page":"105489","intvolume":"       136","citation":{"apa":"Grimme, C., Kerschke, P., Aspar, P., Trautmann, H., Preuss, M., Deutz, A. H., Wang, H., &#38; Emmerich, M. (2021). Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization. <i>Computers &#38; Operations Research</i>, <i>136</i>, 105489. <a href=\"https://doi.org/10.1016/j.cor.2021.105489\">https://doi.org/10.1016/j.cor.2021.105489</a>","bibtex":"@article{Grimme_Kerschke_Aspar_Trautmann_Preuss_Deutz_Wang_Emmerich_2021, title={Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization}, volume={136}, DOI={<a href=\"https://doi.org/10.1016/j.cor.2021.105489\">https://doi.org/10.1016/j.cor.2021.105489</a>}, journal={Computers &#38; Operations Research}, author={Grimme, Christian and Kerschke, Pascal and Aspar, Pelin and Trautmann, Heike and Preuss, Mike and Deutz, André H. and Wang, Hao and Emmerich, Michael}, year={2021}, pages={105489} }","mla":"Grimme, Christian, et al. “Peeking beyond Peaks: Challenges and Research Potentials of Continuous Multimodal Multi-Objective Optimization.” <i>Computers &#38; Operations Research</i>, vol. 136, 2021, p. 105489, doi:<a href=\"https://doi.org/10.1016/j.cor.2021.105489\">https://doi.org/10.1016/j.cor.2021.105489</a>.","short":"C. Grimme, P. Kerschke, P. Aspar, H. Trautmann, M. Preuss, A.H. Deutz, H. Wang, M. Emmerich, Computers &#38; Operations Research 136 (2021) 105489.","ieee":"C. Grimme <i>et al.</i>, “Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization,” <i>Computers &#38; Operations Research</i>, vol. 136, p. 105489, 2021, doi: <a href=\"https://doi.org/10.1016/j.cor.2021.105489\">https://doi.org/10.1016/j.cor.2021.105489</a>.","chicago":"Grimme, Christian, Pascal Kerschke, Pelin Aspar, Heike Trautmann, Mike Preuss, André H. Deutz, Hao Wang, and Michael Emmerich. “Peeking beyond Peaks: Challenges and Research Potentials of Continuous Multimodal Multi-Objective Optimization.” <i>Computers &#38; Operations Research</i> 136 (2021): 105489. <a href=\"https://doi.org/10.1016/j.cor.2021.105489\">https://doi.org/10.1016/j.cor.2021.105489</a>.","ama":"Grimme C, Kerschke P, Aspar P, et al. Peeking beyond peaks: Challenges and research potentials of continuous multimodal multi-objective optimization. <i>Computers &#38; Operations Research</i>. 2021;136:105489. doi:<a href=\"https://doi.org/10.1016/j.cor.2021.105489\">https://doi.org/10.1016/j.cor.2021.105489</a>"},"_id":"46318","department":[{"_id":"34"},{"_id":"819"}],"user_id":"15504","keyword":["Multimodal optimization","Multi-objective continuous optimization","Landscape analysis","Visualization","Benchmarking","Theory","Algorithms"],"language":[{"iso":"eng"}],"publication":"Computers & Operations Research","type":"journal_article","abstract":[{"lang":"eng","text":"Multi-objective (MO) optimization, i.e., the simultaneous optimization of multiple conflicting objectives, is gaining more and more attention in various research areas, such as evolutionary computation, machine learning (e.g., (hyper-)parameter optimization), or logistics (e.g., vehicle routing). Many works in this domain mention the structural problem property of multimodality as a challenge from two classical perspectives: (1) finding all globally optimal solution sets, and (2) avoiding to get trapped in local optima. Interestingly, these streams seem to transfer many traditional concepts of single-objective (SO) optimization into claims, assumptions, or even terminology regarding the MO domain, but mostly neglect the understanding of the structural properties as well as the algorithmic search behavior on a problem’s landscape. However, some recent works counteract this trend, by investigating the fundamentals and characteristics of MO problems using new visualization techniques and gaining surprising insights. Using these visual insights, this work proposes a step towards a unified terminology to capture multimodality and locality in a broader way than it is usually done. This enables us to investigate current research activities in multimodal continuous MO optimization and to highlight new implications and promising research directions for the design of benchmark suites, the discovery of MO landscape features, the development of new MO (or even SO) optimization algorithms, and performance indicators. For all these topics, we provide a review of ideas and methods but also an outlook on future challenges, research potential and perspectives that result from recent developments."}],"status":"public"}]