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Bhatnagar, “A generalization of the Borkar-Meyn theorem for stochastic recursive inclusions,” <i>Mathematics of Operations Research</i>, vol. 42, no. 3, pp. 648–661, 2017.","bibtex":"@article{Ramaswamy_Bhatnagar_2017, title={A generalization of the Borkar-Meyn theorem for stochastic recursive inclusions}, volume={42}, number={3}, journal={Mathematics of Operations Research}, publisher={INFORMS}, author={Ramaswamy, Arunselvan and Bhatnagar, Shalabh}, year={2017}, pages={648–661} }","mla":"Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “A Generalization of the Borkar-Meyn Theorem for Stochastic Recursive Inclusions.” <i>Mathematics of Operations Research</i>, vol. 42, no. 3, INFORMS, 2017, pp. 648–61.","short":"A. Ramaswamy, S. Bhatnagar, Mathematics of Operations Research 42 (2017) 648–661.","apa":"Ramaswamy, A., &#38; Bhatnagar, S. (2017). A generalization of the Borkar-Meyn theorem for stochastic recursive inclusions. <i>Mathematics of Operations Research</i>, <i>42</i>(3), 648–661."},"intvolume":"        42","page":"648-661","issue":"3","extern":"1","language":[{"iso":"eng"}],"_id":"24153","user_id":"66937","department":[{"_id":"355"}],"status":"public","type":"journal_article","publication":"Mathematics of Operations Research"},{"doi":"10.5445/KSP/1000074341","title":"Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics","author":[{"first_name":"Vitalik","full_name":"Melnikov, Vitalik","last_name":"Melnikov"},{"last_name":"Hüllermeier","id":"48129","full_name":"Hüllermeier, Eyke","first_name":"Eyke"}],"date_created":"2018-06-25T08:14:49Z","date_updated":"2022-01-06T06:59:10Z","publisher":"KIT Scientific Publishing","citation":{"ama":"Melnikov V, Hüllermeier E. Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics. In: <i>Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. - 24. November 2017</i>. KIT Scientific Publishing; 2017. doi:<a href=\"https://doi.org/10.5445/KSP/1000074341\">10.5445/KSP/1000074341</a>","chicago":"Melnikov, Vitalik, and Eyke Hüllermeier. “Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics.” In <i>Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. - 24. November 2017</i>. KIT Scientific Publishing, 2017. <a href=\"https://doi.org/10.5445/KSP/1000074341\">https://doi.org/10.5445/KSP/1000074341</a>.","ieee":"V. Melnikov and E. Hüllermeier, “Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics,” in <i>Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. - 24. November 2017</i>, 2017.","apa":"Melnikov, V., &#38; Hüllermeier, E. (2017). Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics. In <i>Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. - 24. November 2017</i>. KIT Scientific Publishing. <a href=\"https://doi.org/10.5445/KSP/1000074341\">https://doi.org/10.5445/KSP/1000074341</a>","mla":"Melnikov, Vitalik, and Eyke Hüllermeier. “Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics.” <i>Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. - 24. November 2017</i>, KIT Scientific Publishing, 2017, doi:<a href=\"https://doi.org/10.5445/KSP/1000074341\">10.5445/KSP/1000074341</a>.","short":"V. Melnikov, E. Hüllermeier, in: Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. - 24. November 2017, KIT Scientific Publishing, 2017.","bibtex":"@inproceedings{Melnikov_Hüllermeier_2017, title={Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics}, DOI={<a href=\"https://doi.org/10.5445/KSP/1000074341\">10.5445/KSP/1000074341</a>}, booktitle={Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. - 24. November 2017}, publisher={KIT Scientific Publishing}, author={Melnikov, Vitalik and Hüllermeier, Eyke}, year={2017} }"},"year":"2017","has_accepted_license":"1","file_date_updated":"2018-11-30T09:47:59Z","language":[{"iso":"eng"}],"ddc":["000"],"user_id":"15504","department":[{"_id":"355"}],"project":[{"name":"SFB 901 - Subproject B3","_id":"11"},{"name":"SFB 901 - Project Area B","_id":"3"},{"_id":"1","name":"SFB 901"}],"_id":"3325","file":[{"file_size":1829552,"file_id":"5987","file_name":"main.pdf","access_level":"closed","date_updated":"2018-11-30T09:47:59Z","date_created":"2018-11-30T09:47:59Z","creator":"melnikov","success":1,"relation":"main_file","content_type":"application/pdf"}],"status":"public","type":"conference","publication":"Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. - 24. November 2017"},{"status":"public","editor":[{"last_name":"Marcelo De Barros, Janusz Klink,Tadeus Uhl","full_name":"Marcelo De Barros, Janusz Klink,Tadeus Uhl, Thomas Prinz","first_name":"Thomas Prinz"}],"type":"conference","file_date_updated":"2018-03-21T13:04:12Z","user_id":"477","department":[{"_id":"77"},{"_id":"355"},{"_id":"179"}],"project":[{"_id":"1","name":"SFB 901"},{"_id":"10","name":"SFB 901 - Subprojekt B2"},{"name":"SFB 901 - Subproject B3","_id":"11"},{"_id":"12","name":"SFB 901 - Subproject B4"},{"_id":"8","name":"SFB 901 - Subproject A4"},{"name":"SFB 901 - Project Area A","_id":"2"},{"name":"SFB 901 - Project Area B","_id":"3"}],"_id":"115","citation":{"ama":"Jakobs M-C, Krämer J, van Straaten D, Lettmann T. Certification Matters for Service Markets. In: Marcelo De Barros, Janusz Klink,Tadeus Uhl TP, ed. <i>The Ninth International Conferences on Advanced Service Computing (SERVICE COMPUTATION)</i>. ; 2017:7-12.","chicago":"Jakobs, Marie-Christine, Julia Krämer, Dirk van Straaten, and Theodor Lettmann. “Certification Matters for Service Markets.” In <i>The Ninth International Conferences on Advanced Service Computing (SERVICE COMPUTATION)</i>, edited by Thomas Prinz Marcelo De Barros, Janusz Klink,Tadeus Uhl, 7–12, 2017.","ieee":"M.-C. Jakobs, J. Krämer, D. van Straaten, and T. Lettmann, “Certification Matters for Service Markets,” in <i>The Ninth International Conferences on Advanced Service Computing (SERVICE COMPUTATION)</i>, 2017, pp. 7–12.","short":"M.-C. Jakobs, J. Krämer, D. van Straaten, T. Lettmann, in: T.P. Marcelo De Barros, Janusz Klink,Tadeus Uhl (Ed.), The Ninth International Conferences on Advanced Service Computing (SERVICE COMPUTATION), 2017, pp. 7–12.","bibtex":"@inproceedings{Jakobs_Krämer_van Straaten_Lettmann_2017, title={Certification Matters for Service Markets}, booktitle={The Ninth International Conferences on Advanced Service Computing (SERVICE COMPUTATION)}, author={Jakobs, Marie-Christine and Krämer, Julia and van Straaten, Dirk and Lettmann, Theodor}, editor={Marcelo De Barros, Janusz Klink,Tadeus Uhl, Thomas PrinzEditor}, year={2017}, pages={7–12} }","mla":"Jakobs, Marie-Christine, et al. “Certification Matters for Service Markets.” <i>The Ninth International Conferences on Advanced Service Computing (SERVICE COMPUTATION)</i>, edited by Thomas Prinz Marcelo De Barros, Janusz Klink,Tadeus Uhl, 2017, pp. 7–12.","apa":"Jakobs, M.-C., Krämer, J., van Straaten, D., &#38; Lettmann, T. (2017). Certification Matters for Service Markets. In T. P. Marcelo De Barros, Janusz Klink,Tadeus Uhl (Ed.), <i>The Ninth International Conferences on Advanced Service Computing (SERVICE COMPUTATION)</i> (pp. 7–12)."},"page":"7-12","has_accepted_license":"1","author":[{"last_name":"Jakobs","full_name":"Jakobs, Marie-Christine","first_name":"Marie-Christine"},{"first_name":"Julia","full_name":"Krämer, Julia","last_name":"Krämer"},{"last_name":"van Straaten","id":"10311","full_name":"van Straaten, Dirk","first_name":"Dirk"},{"orcid":"0000-0001-5859-2457","last_name":"Lettmann","full_name":"Lettmann, Theodor","id":"315","first_name":"Theodor"}],"date_updated":"2022-01-06T06:51:02Z","file":[{"date_updated":"2018-03-21T13:04:12Z","creator":"florida","date_created":"2018-03-21T13:04:12Z","file_size":133531,"file_name":"115-JakobsKraemerVanStraatenLettmann2017.pdf","file_id":"1564","access_level":"closed","content_type":"application/pdf","success":1,"relation":"main_file"}],"abstract":[{"text":"Whenever customers have to decide between different instances of the same product, they are interested in buying the best product. In contrast, companies are interested in reducing the construction effort (and usually as a consequence thereof, the quality) to gain profit. The described setting is widely known as opposed preferences in quality of the product and also applies to the context of service-oriented computing. In general, service-oriented computing emphasizes the construction of large software systems out of existing services, where services are small and self-contained pieces of software that adhere to a specified interface. Several implementations of the same interface are considered as several instances of the same service. Thereby, customers are interested in buying the best service implementation for their service composition wrt. to metrics, such as costs, energy, memory consumption, or execution time. One way to ensure the service quality is to employ certificates, which can come in different kinds: Technical certificates proving correctness can be automatically constructed by the service provider and again be automatically checked by the user. Digital certificates allow proof of the integrity of a product. Other certificates might be rolled out if service providers follow a good software construction principle, which is checked in annual audits. Whereas all of these certificates are handled differently in service markets, what they have in common is that they influence the buying decisions of customers. In this paper, we review state-of-the-art developments in certification with respect to service-oriented computing. We not only discuss how certificates are constructed and handled in service-oriented computing but also review the effects of certificates on the market from an economic perspective.","lang":"eng"}],"publication":"The Ninth International Conferences on Advanced Service Computing (SERVICE COMPUTATION)","language":[{"iso":"eng"}],"ddc":["040"],"year":"2017","title":"Certification Matters for Service Markets","date_created":"2017-10-17T12:41:14Z"},{"language":[{"iso":"eng"}],"publication":"Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature","abstract":[{"lang":"eng","text":"In this paper, we present the annotation challenges we have encountered when working on a historical language that was undergoing elaboration processes. We especially focus on syntactic ambiguity and gradience in Middle Low German, which causes uncertainty to some extent. Since current annotation tools consider construction contexts and the dynamics of the grammaticalization only partially, we plan to extend CorA – a web-based annotation tool for historical and other non-standard language data – to capture elaboration phenomena and annotator unsureness. Moreover, we seek to interactively learn morphological as well as syntactic annotations."}],"publisher":"Association for Computational Linguistics (ACL)","date_created":"2018-01-31T15:32:33Z","title":"Annotation Challenges for Reconstructing the Structural Elaboration of Middle Low German","quality_controlled":"1","year":"2017","project":[{"_id":"39","name":"InterGramm"}],"_id":"1158","user_id":"13929","department":[{"_id":"36"},{"_id":"579"},{"_id":"115"},{"_id":"355"},{"_id":"615"}],"type":"conference","status":"public","date_updated":"2022-01-06T06:51:03Z","author":[{"full_name":"Seemann, Nina","id":"65408","last_name":"Seemann","first_name":"Nina"},{"full_name":"Merten, Marie-Luis","last_name":"Merten","first_name":"Marie-Luis"},{"full_name":"Geierhos, Michaela","id":"42496","last_name":"Geierhos","orcid":"0000-0002-8180-5606","first_name":"Michaela"},{"last_name":"Tophinke","full_name":"Tophinke, Doris","first_name":"Doris"},{"full_name":"Hüllermeier, Eyke","last_name":"Hüllermeier","first_name":"Eyke"}],"doi":"10.18653/v1/W17-2206","conference":{"start_date":"2017-07-31","name":"Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCH-CLfL 2017)","location":"Vancouver, BC, Canada","end_date":"2017-08-04"},"publication_status":"published","place":"Stroudsburg, PA, USA","citation":{"apa":"Seemann, N., Merten, M.-L., Geierhos, M., Tophinke, D., &#38; Hüllermeier, E. (2017). Annotation Challenges for Reconstructing the Structural Elaboration of Middle Low German. In <i>Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature</i> (pp. 40–45). Stroudsburg, PA, USA: Association for Computational Linguistics (ACL). <a href=\"https://doi.org/10.18653/v1/W17-2206\">https://doi.org/10.18653/v1/W17-2206</a>","bibtex":"@inproceedings{Seemann_Merten_Geierhos_Tophinke_Hüllermeier_2017, place={Stroudsburg, PA, USA}, title={Annotation Challenges for Reconstructing the Structural Elaboration of Middle Low German}, DOI={<a href=\"https://doi.org/10.18653/v1/W17-2206\">10.18653/v1/W17-2206</a>}, booktitle={Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature}, publisher={Association for Computational Linguistics (ACL)}, author={Seemann, Nina and Merten, Marie-Luis and Geierhos, Michaela and Tophinke, Doris and Hüllermeier, Eyke}, year={2017}, pages={40–45} }","short":"N. Seemann, M.-L. Merten, M. Geierhos, D. Tophinke, E. Hüllermeier, in: Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, Association for Computational Linguistics (ACL), Stroudsburg, PA, USA, 2017, pp. 40–45.","mla":"Seemann, Nina, et al. “Annotation Challenges for Reconstructing the Structural Elaboration of Middle Low German.” <i>Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature</i>, Association for Computational Linguistics (ACL), 2017, pp. 40–45, doi:<a href=\"https://doi.org/10.18653/v1/W17-2206\">10.18653/v1/W17-2206</a>.","ieee":"N. Seemann, M.-L. Merten, M. Geierhos, D. Tophinke, and E. Hüllermeier, “Annotation Challenges for Reconstructing the Structural Elaboration of Middle Low German,” in <i>Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature</i>, Vancouver, BC, Canada, 2017, pp. 40–45.","chicago":"Seemann, Nina, Marie-Luis Merten, Michaela Geierhos, Doris Tophinke, and Eyke Hüllermeier. “Annotation Challenges for Reconstructing the Structural Elaboration of Middle Low German.” In <i>Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature</i>, 40–45. Stroudsburg, PA, USA: Association for Computational Linguistics (ACL), 2017. <a href=\"https://doi.org/10.18653/v1/W17-2206\">https://doi.org/10.18653/v1/W17-2206</a>.","ama":"Seemann N, Merten M-L, Geierhos M, Tophinke D, Hüllermeier E. Annotation Challenges for Reconstructing the Structural Elaboration of Middle Low German. In: <i>Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature</i>. Stroudsburg, PA, USA: Association for Computational Linguistics (ACL); 2017:40-45. doi:<a href=\"https://doi.org/10.18653/v1/W17-2206\">10.18653/v1/W17-2206</a>"},"page":"40-45"},{"citation":{"ieee":"N. N. Schnitker, <i>Genetischer Algorithmus zur Erstellung von Ensembles von Nested Dichotomies</i>. Universität Paderborn, 2017.","chicago":"Schnitker, Nino Noel. <i>Genetischer Algorithmus zur Erstellung von Ensembles von Nested Dichotomies</i>. Universität Paderborn, 2017.","ama":"Schnitker NN. <i>Genetischer Algorithmus zur Erstellung von Ensembles von Nested Dichotomies</i>. Universität Paderborn; 2017.","bibtex":"@book{Schnitker_2017, title={Genetischer Algorithmus zur Erstellung von Ensembles von Nested Dichotomies}, publisher={Universität Paderborn}, author={Schnitker, Nino Noel}, year={2017} }","short":"N.N. Schnitker, Genetischer Algorithmus zur Erstellung von Ensembles von Nested Dichotomies, Universität Paderborn, 2017.","mla":"Schnitker, Nino Noel. <i>Genetischer Algorithmus zur Erstellung von Ensembles von Nested Dichotomies</i>. Universität Paderborn, 2017.","apa":"Schnitker, N. N. (2017). <i>Genetischer Algorithmus zur Erstellung von Ensembles von Nested Dichotomies</i>. Universität Paderborn."},"year":"2017","date_created":"2018-11-15T08:10:48Z","supervisor":[{"first_name":"Eyke","last_name":"Hüllermeier","full_name":"Hüllermeier, Eyke","id":"48129"}],"author":[{"first_name":"Nino Noel","full_name":"Schnitker, Nino Noel","last_name":"Schnitker"}],"date_updated":"2022-01-06T07:02:35Z","publisher":"Universität Paderborn","title":"Genetischer Algorithmus zur Erstellung von Ensembles von Nested Dichotomies","type":"bachelorsthesis","status":"public","user_id":"477","department":[{"_id":"355"}],"project":[{"_id":"1","name":"SFB 901"},{"_id":"3","name":"SFB 901 - Project Area B"},{"_id":"10","name":"SFB 901 - Subproject B2"}],"_id":"5694","language":[{"iso":"ger"}]},{"citation":{"ieee":"P. Gupta <i>et al.</i>, “jPL: A Java-based Software Framework for Preference Learning,” presented at the WDA 2017 Workshops: KDML, FGWM, IR, and FGDB, Rostock, 2017.","chicago":"Gupta, Pritha, Alexander Hetzer, Tanja Tornede, Sebastian Gottschalk, Andreas Kornelsen, Sebastian Osterbrink, Karlson Pfannschmidt, and Eyke Hüllermeier. “JPL: A Java-Based Software Framework for Preference Learning,” 2017.","ama":"Gupta P, Hetzer A, Tornede T, et al. jPL: A Java-based Software Framework for Preference Learning. In: ; 2017.","mla":"Gupta, Pritha, et al. <i>JPL: A Java-Based Software Framework for Preference Learning</i>. 2017.","short":"P. Gupta, A. Hetzer, T. Tornede, S. Gottschalk, A. Kornelsen, S. Osterbrink, K. Pfannschmidt, E. Hüllermeier, in: 2017.","bibtex":"@inproceedings{Gupta_Hetzer_Tornede_Gottschalk_Kornelsen_Osterbrink_Pfannschmidt_Hüllermeier_2017, title={jPL: A Java-based Software Framework for Preference Learning}, author={Gupta, Pritha and Hetzer, Alexander and Tornede, Tanja and Gottschalk, Sebastian and Kornelsen, Andreas and Osterbrink, Sebastian and Pfannschmidt, Karlson and Hüllermeier, Eyke}, year={2017} }","apa":"Gupta, P., Hetzer, A., Tornede, T., Gottschalk, S., Kornelsen, A., Osterbrink, S., … Hüllermeier, E. (2017). jPL: A Java-based Software Framework for Preference Learning. Presented at the WDA 2017 Workshops: KDML, FGWM, IR, and FGDB, Rostock."},"year":"2017","conference":{"end_date":"13.09.2017","location":"Rostock","name":"WDA 2017 Workshops: KDML, FGWM, IR, and FGDB","start_date":"11.09.2017"},"title":"jPL: A Java-based Software Framework for Preference Learning","date_created":"2018-11-19T07:32:31Z","author":[{"full_name":"Gupta, Pritha","last_name":"Gupta","first_name":"Pritha"},{"first_name":"Alexander","full_name":"Hetzer, Alexander","id":"38209","last_name":"Hetzer"},{"first_name":"Tanja","last_name":"Tornede","full_name":"Tornede, Tanja"},{"last_name":"Gottschalk","full_name":"Gottschalk, Sebastian","first_name":"Sebastian"},{"first_name":"Andreas","full_name":"Kornelsen, Andreas","last_name":"Kornelsen"},{"first_name":"Sebastian","last_name":"Osterbrink","full_name":"Osterbrink, Sebastian"},{"first_name":"Karlson","last_name":"Pfannschmidt","full_name":"Pfannschmidt, Karlson"},{"first_name":"Eyke","full_name":"Hüllermeier, Eyke","last_name":"Hüllermeier"}],"date_updated":"2022-01-06T07:02:37Z","status":"public","type":"conference_abstract","language":[{"iso":"eng"}],"extern":"1","department":[{"_id":"355"}],"user_id":"38209","_id":"5722"},{"status":"public","type":"mastersthesis","language":[{"iso":"eng"}],"_id":"5724","project":[{"_id":"1","name":"SFB 901"},{"name":"SFB 901 - Project Area B","_id":"3"},{"_id":"10","name":"SFB 901 - Subproject B2"}],"department":[{"_id":"355"},{"_id":"199"}],"user_id":"477","year":"2017","citation":{"chicago":"Hetzer, Alexander, and Tanja Tornede. <i>Solving the Container Pre-Marshalling Problem Using Reinforcement Learning and Structured Output Prediction</i>. Universität Paderborn, 2017.","ieee":"A. Hetzer and T. Tornede, <i>Solving the Container Pre-Marshalling Problem using Reinforcement Learning and Structured Output Prediction</i>. Universität Paderborn, 2017.","ama":"Hetzer A, Tornede T. <i>Solving the Container Pre-Marshalling Problem Using Reinforcement Learning and Structured Output Prediction</i>. Universität Paderborn; 2017.","bibtex":"@book{Hetzer_Tornede_2017, title={Solving the Container Pre-Marshalling Problem using Reinforcement Learning and Structured Output Prediction}, publisher={Universität Paderborn}, author={Hetzer, Alexander and Tornede, Tanja}, year={2017} }","mla":"Hetzer, Alexander, and Tanja Tornede. <i>Solving the Container Pre-Marshalling Problem Using Reinforcement Learning and Structured Output Prediction</i>. Universität Paderborn, 2017.","short":"A. Hetzer, T. Tornede, Solving the Container Pre-Marshalling Problem Using Reinforcement Learning and Structured Output Prediction, Universität Paderborn, 2017.","apa":"Hetzer, A., &#38; Tornede, T. (2017). <i>Solving the Container Pre-Marshalling Problem using Reinforcement Learning and Structured Output Prediction</i>. Universität Paderborn."},"title":"Solving the Container Pre-Marshalling Problem using Reinforcement Learning and Structured Output Prediction","publisher":"Universität Paderborn","date_updated":"2022-01-06T07:02:37Z","supervisor":[{"first_name":"Felix","full_name":"Mohr, Felix","last_name":"Mohr"},{"id":"48129","full_name":"Hüllermeier, Eyke","last_name":"Hüllermeier","first_name":"Eyke"},{"first_name":"Kevin","full_name":"Tierney, Kevin","last_name":"Tierney"}],"date_created":"2018-11-19T07:49:13Z","author":[{"first_name":"Alexander","id":"38209","full_name":"Hetzer, Alexander","last_name":"Hetzer"},{"full_name":"Tornede, Tanja","last_name":"Tornede","first_name":"Tanja"}]},{"ddc":["000"],"file_date_updated":"2018-11-02T14:24:29Z","language":[{"iso":"eng"}],"_id":"71","project":[{"_id":"1","name":"SFB 901"},{"_id":"12","name":"SFB 901 - Subprojekt B4"},{"name":"SFB 901 - Subproject B2","_id":"10"},{"name":"SFB 901 - Project Area B","_id":"3"},{"_id":"11","name":"SFB 901 - Subproject B3"}],"department":[{"_id":"355"},{"_id":"77"}],"user_id":"15504","series_title":"SWAN'17","abstract":[{"lang":"eng","text":"Today, software verification tools have reached the maturity to be used for large scale programs. Different tools perform differently well on varying code. A software developer is hence faced with the problem of choosing a tool appropriate for her program at hand. A ranking of tools on programs could facilitate the choice. Such rankings can, however, so far only be obtained by running all considered tools on the program.In this paper, we present a machine learning approach to predicting rankings of tools on programs. The method builds upon so-called label ranking algorithms, which we complement with appropriate kernels providing a similarity measure for programs. Our kernels employ a graph representation for software source code that mixes elements of control flow and program dependence graphs with abstract syntax trees. Using data sets from the software verification competition SV-COMP, we demonstrate our rank prediction technique to generalize well and achieve a rather high predictive accuracy (rank correlation > 0.6)."}],"status":"public","file":[{"file_name":"fsews17swan-swanmain1.pdf","access_level":"closed","file_id":"5271","file_size":822383,"date_created":"2018-11-02T14:24:29Z","creator":"ups","date_updated":"2018-11-02T14:24:29Z","relation":"main_file","success":1,"content_type":"application/pdf"}],"publication":"Proceedings of the 3rd International Workshop on Software Analytics","type":"conference","title":"Predicting Rankings of Software Verification Tools","doi":"10.1145/3121257.3121262","date_updated":"2022-01-06T07:03:28Z","author":[{"first_name":"Mike","full_name":"Czech, Mike","last_name":"Czech"},{"first_name":"Eyke","last_name":"Hüllermeier","id":"48129","full_name":"Hüllermeier, Eyke"},{"full_name":"Jakobs, Marie-Christine","last_name":"Jakobs","first_name":"Marie-Christine"},{"first_name":"Heike","full_name":"Wehrheim, Heike","id":"573","last_name":"Wehrheim"}],"date_created":"2017-10-17T12:41:05Z","year":"2017","page":"23-26","citation":{"ama":"Czech M, Hüllermeier E, Jakobs M-C, Wehrheim H. Predicting Rankings of Software Verification Tools. In: <i>Proceedings of the 3rd International Workshop on Software Analytics</i>. SWAN’17. ; 2017:23-26. doi:<a href=\"https://doi.org/10.1145/3121257.3121262\">10.1145/3121257.3121262</a>","chicago":"Czech, Mike, Eyke Hüllermeier, Marie-Christine Jakobs, and Heike Wehrheim. “Predicting Rankings of Software Verification Tools.” In <i>Proceedings of the 3rd International Workshop on Software Analytics</i>, 23–26. SWAN’17, 2017. <a href=\"https://doi.org/10.1145/3121257.3121262\">https://doi.org/10.1145/3121257.3121262</a>.","ieee":"M. Czech, E. Hüllermeier, M.-C. Jakobs, and H. Wehrheim, “Predicting Rankings of Software Verification Tools,” in <i>Proceedings of the 3rd International Workshop on Software Analytics</i>, 2017, pp. 23–26.","apa":"Czech, M., Hüllermeier, E., Jakobs, M.-C., &#38; Wehrheim, H. (2017). Predicting Rankings of Software Verification Tools. In <i>Proceedings of the 3rd International Workshop on Software Analytics</i> (pp. 23–26). <a href=\"https://doi.org/10.1145/3121257.3121262\">https://doi.org/10.1145/3121257.3121262</a>","short":"M. Czech, E. Hüllermeier, M.-C. Jakobs, H. Wehrheim, in: Proceedings of the 3rd International Workshop on Software Analytics, 2017, pp. 23–26.","bibtex":"@inproceedings{Czech_Hüllermeier_Jakobs_Wehrheim_2017, series={SWAN’17}, title={Predicting Rankings of Software Verification Tools}, DOI={<a href=\"https://doi.org/10.1145/3121257.3121262\">10.1145/3121257.3121262</a>}, booktitle={Proceedings of the 3rd International Workshop on Software Analytics}, author={Czech, Mike and Hüllermeier, Eyke and Jakobs, Marie-Christine and Wehrheim, Heike}, year={2017}, pages={23–26}, collection={SWAN’17} }","mla":"Czech, Mike, et al. “Predicting Rankings of Software Verification Tools.” <i>Proceedings of the 3rd International Workshop on Software Analytics</i>, 2017, pp. 23–26, doi:<a href=\"https://doi.org/10.1145/3121257.3121262\">10.1145/3121257.3121262</a>."},"has_accepted_license":"1"},{"ddc":["000"],"file_date_updated":"2018-11-21T10:50:11Z","language":[{"iso":"eng"}],"project":[{"name":"SFB 901","_id":"1"},{"_id":"11","name":"SFB 901 - Subprojekt B3"},{"name":"SFB 901 - Subprojekt B4","_id":"12"},{"name":"SFB 901 - Project Area B","_id":"3"}],"_id":"72","user_id":"15504","department":[{"_id":"77"},{"_id":"355"}],"abstract":[{"text":"Software verification competitions, such as the annual SV-COMP, evaluate software verification tools with respect to their effectivity and efficiency. Typically, the outcome of a competition is a (possibly category-specific) ranking of the tools. For many applications, such as building portfolio solvers, it would be desirable to have an idea of the (relative) performance of verification tools on a given verification task beforehand, i.e., prior to actually running all tools on the task.In this paper, we present a machine learning approach to predicting rankings of tools on verification tasks. The method builds upon so-called label ranking algorithms, which we complement with appropriate kernels providing a similarity measure for verification tasks. Our kernels employ a graph representation for software source code that mixes elements of control flow and program dependence graphs with abstract syntax trees. Using data sets from SV-COMP, we demonstrate our rank prediction technique to generalize well and achieve a rather high predictive accuracy. In particular, our method outperforms a recently proposed feature-based approach of Demyanova et al. (when applied to rank predictions). 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Czech, E. Hüllermeier, M.-C. Jakobs, and H. Wehrheim, <i>Predicting Rankings of Software Verification Competitions</i>. 2017.","chicago":"Czech, Mike, Eyke Hüllermeier, Marie-Christine Jakobs, and Heike Wehrheim. <i>Predicting Rankings of Software Verification Competitions</i>, 2017.","mla":"Czech, Mike, et al. <i>Predicting Rankings of Software Verification Competitions</i>. 2017.","bibtex":"@book{Czech_Hüllermeier_Jakobs_Wehrheim_2017, title={Predicting Rankings of Software Verification Competitions}, author={Czech, Mike and Hüllermeier, Eyke and Jakobs, Marie-Christine and Wehrheim, Heike}, year={2017} }","short":"M. Czech, E. Hüllermeier, M.-C. Jakobs, H. Wehrheim, Predicting Rankings of Software Verification Competitions, 2017.","apa":"Czech, M., Hüllermeier, E., Jakobs, M.-C., &#38; Wehrheim, H. 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Hüllermeier, in: Encyclopedia of Machine Learning and Data Mining, 2017, pp. 1000–1005.","ieee":"J. Fürnkranz and E. Hüllermeier, “Preference Learning,” in <i>Encyclopedia of Machine Learning and Data Mining</i>, 2017, pp. 1000–1005.","chicago":"Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” In <i>Encyclopedia of Machine Learning and Data Mining</i>, 1000–1005, 2017.","ama":"Fürnkranz J, Hüllermeier E. Preference Learning. In: <i>Encyclopedia of Machine Learning and Data Mining</i>. ; 2017:1000-1005."},"title":"Preference Learning","date_updated":"2022-01-06T06:50:45Z","author":[{"last_name":"Fürnkranz","full_name":"Fürnkranz, J.","first_name":"J."},{"full_name":"Hüllermeier, Eyke","id":"48129","last_name":"Hüllermeier","first_name":"Eyke"}],"date_created":"2019-07-09T15:37:09Z"},{"language":[{"iso":"eng"}],"user_id":"49109","department":[{"_id":"34"},{"_id":"7"},{"_id":"355"}],"_id":"10784","status":"public","editor":[{"first_name":"C.","full_name":"Sammut, C.","last_name":"Sammut"},{"first_name":"G.I.","full_name":"Webb, G.I.","last_name":"Webb"}],"type":"book_chapter","publication":"Encyclopedia of Machine Learning and Data Mining","title":"Preference Learning","date_created":"2019-07-10T15:44:32Z","author":[{"first_name":"J.","last_name":"Fürnkranz","full_name":"Fürnkranz, J."},{"first_name":"Eyke","full_name":"Hüllermeier, Eyke","id":"48129","last_name":"Hüllermeier"}],"volume":107,"publisher":"Springer","date_updated":"2022-01-06T06:50:50Z","citation":{"apa":"Fürnkranz, J., &#38; Hüllermeier, E. (2017). Preference Learning. In C. Sammut &#38; G. I. Webb (Eds.), <i>Encyclopedia of Machine Learning and Data Mining</i> (Vol. 107, pp. 1000–1005). Springer.","mla":"Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” <i>Encyclopedia of Machine Learning and Data Mining</i>, edited by C. Sammut and G.I. Webb, vol. 107, Springer, 2017, pp. 1000–05.","short":"J. Fürnkranz, E. Hüllermeier, in: C. Sammut, G.I. Webb (Eds.), Encyclopedia of Machine Learning and Data Mining, Springer, 2017, pp. 1000–1005.","bibtex":"@inbook{Fürnkranz_Hüllermeier_2017, title={Preference Learning}, volume={107}, booktitle={Encyclopedia of Machine Learning and Data Mining}, publisher={Springer}, author={Fürnkranz, J. and Hüllermeier, Eyke}, editor={Sammut, C. and Webb, G.I.Editors}, year={2017}, pages={1000–1005} }","chicago":"Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” In <i>Encyclopedia of Machine Learning and Data Mining</i>, edited by C. Sammut and G.I. Webb, 107:1000–1005. Springer, 2017.","ieee":"J. Fürnkranz and E. Hüllermeier, “Preference Learning,” in <i>Encyclopedia of Machine Learning and Data Mining</i>, vol. 107, C. Sammut and G. I. Webb, Eds. Springer, 2017, pp. 1000–1005.","ama":"Fürnkranz J, Hüllermeier E. Preference Learning. In: Sammut C, Webb GI, eds. <i>Encyclopedia of Machine Learning and Data Mining</i>. Vol 107. Springer; 2017:1000-1005."},"page":"1000-1005","intvolume":"       107","year":"2017"},{"file_date_updated":"2018-11-06T15:28:09Z","department":[{"_id":"355"}],"user_id":"49109","_id":"1180","project":[{"_id":"1","name":"SFB 901"},{"name":"SFB 901 - Project Area B","_id":"3"},{"name":"SFB 901 - Subproject B2","_id":"10"}],"status":"public","type":"conference","conference":{"end_date":"2017-11-24","location":"Dortmund","name":"27th Workshop Computational Intelligence","start_date":"2017-11-23"},"main_file_link":[{"open_access":"1","url":"https://publikationen.bibliothek.kit.edu/1000074341/4643874"}],"author":[{"orcid":" https://orcid.org/0000-0001-9782-6818","last_name":"Wever","full_name":"Wever, Marcel Dominik","id":"33176","first_name":"Marcel Dominik"},{"first_name":"Felix","last_name":"Mohr","full_name":"Mohr, Felix"},{"id":"48129","full_name":"Hüllermeier, Eyke","last_name":"Hüllermeier","first_name":"Eyke"}],"date_updated":"2022-01-06T06:51:09Z","oa":"1","citation":{"apa":"Wever, M. D., Mohr, F., &#38; Hüllermeier, E. (2017). Automatic Machine Learning: Hierachical Planning Versus Evolutionary Optimization. In <i>27th Workshop Computational Intelligence</i>. Dortmund.","short":"M.D. Wever, F. Mohr, E. Hüllermeier, in: 27th Workshop Computational Intelligence, Dortmund, 2017.","mla":"Wever, Marcel Dominik, et al. “Automatic Machine Learning: Hierachical Planning Versus Evolutionary Optimization.” <i>27th Workshop Computational Intelligence</i>, 2017.","bibtex":"@inproceedings{Wever_Mohr_Hüllermeier_2017, place={Dortmund}, title={Automatic Machine Learning: Hierachical Planning Versus Evolutionary Optimization}, booktitle={27th Workshop Computational Intelligence}, author={Wever, Marcel Dominik and Mohr, Felix and Hüllermeier, Eyke}, year={2017} }","ieee":"M. D. Wever, F. Mohr, and E. Hüllermeier, “Automatic Machine Learning: Hierachical Planning Versus Evolutionary Optimization,” in <i>27th Workshop Computational Intelligence</i>, Dortmund, 2017.","chicago":"Wever, Marcel Dominik, Felix Mohr, and Eyke Hüllermeier. “Automatic Machine Learning: Hierachical Planning Versus Evolutionary Optimization.” In <i>27th Workshop Computational Intelligence</i>. Dortmund, 2017.","ama":"Wever MD, Mohr F, Hüllermeier E. Automatic Machine Learning: Hierachical Planning Versus Evolutionary Optimization. In: <i>27th Workshop Computational Intelligence</i>. Dortmund; 2017."},"place":"Dortmund","has_accepted_license":"1","publication_status":"published","language":[{"iso":"eng"}],"ddc":["000"],"file":[{"creator":"wever","date_created":"2018-11-06T15:28:09Z","date_updated":"2018-11-06T15:28:09Z","access_level":"closed","file_id":"5387","file_name":"CI Workshop AutoML.pdf","file_size":323589,"content_type":"application/pdf","relation":"main_file","success":1}],"abstract":[{"text":"These days, there is a strong rise in the needs for machine learning applications, requiring an automation of machine learning engineering which is referred to as AutoML. In AutoML the selection, composition and parametrization of machine learning algorithms is automated and tailored to a specific problem, resulting in a machine learning pipeline. Current approaches reduce the AutoML problem to optimization of hyperparameters. Based on recursive task networks, in this paper we present one approach from the field of automated planning and one evolutionary optimization approach. Instead of simply parametrizing a given pipeline, this allows for structure optimization of machine learning pipelines, as well. We evaluate the two approaches in an extensive evaluation, finding both approaches to have their strengths in different areas. Moreover, the two approaches outperform the state-of-the-art tool Auto-WEKA in many settings.","lang":"eng"}],"publication":"27th Workshop Computational Intelligence","title":"Automatic Machine Learning: Hierachical Planning Versus Evolutionary Optimization","date_created":"2018-02-22T07:19:18Z","year":"2017"}]