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367 Publications
2018 | Bachelorsthesis | LibreCat-ID: 3320
Rautenberg K. Korrektheitsbeweise für Muster von Servicekompositionen. Universität Paderborn; 2018.
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2018 | Conference Paper | LibreCat-ID: 3373
Hansmeier T, Platzner M, Andrews D. An FPGA/HMC-Based Accelerator for Resolution Proof Checking. In: ARC 2018: Applied Reconfigurable Computing. Architectures, Tools, and Applications. Vol 10824. Lecture Notes in Computer Science. Springer International Publishing; 2018:153-165. doi:10.1007/978-3-319-78890-6_13
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2018 | Journal Article | LibreCat-ID: 3402
Melnikov V, Hüllermeier E. On the effectiveness of heuristics for learning nested dichotomies: an empirical analysis. Machine Learning. 2018. doi:10.1007/s10994-018-5733-1
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2018 | Conference Paper | LibreCat-ID: 3414
Börding P, Haltermann JF, Jakobs M-C, Wehrheim H. JMCTest: Automatically Testing Inter-Method Contracts in Java. In: Proceedings of the IFIP International Conference on Testing Software and Systems (ICTSS 2018). Vol 11146. Lecture Notes in Computer Science. Springer; 2018:39--55.
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2018 | Journal Article | LibreCat-ID: 3510 | 
Mohr F, Wever MD, Hüllermeier E. ML-Plan: Automated Machine Learning via Hierarchical Planning. Machine Learning. Published online 2018:1495-1515. doi:10.1007/s10994-018-5735-z
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2018 | Conference Paper | LibreCat-ID: 3552 |
Mohr F, Wever MD, Hüllermeier E. Reduction Stumps for Multi-Class Classification. In: Proceedings of the Symposium on Intelligent Data Analysis. ‘s-Hertogenbosch, the Netherlands. doi:10.1007/978-3-030-01768-2_19
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2018 | Preprint | LibreCat-ID: 3586
Witschen LM, Wiersema T, Ghasemzadeh Mohammadi H, Awais M, Platzner M. CIRCA: Towards a Modular and Extensible Framework for Approximate Circuit Generation. Third Workshop on Approximate Computing (AxC 2018).
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2018 | Dissertation | LibreCat-ID: 3720
Ho N. FPGA-Based Reconfigurable Cache Mapping Schemes: Design and Optimization. Universität Paderborn; 2018. doi:10.17619/UNIPB/1-376
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2018 | Conference Paper | LibreCat-ID: 3852 |
Wever MD, Mohr F, Hüllermeier E. ML-Plan for Unlimited-Length Machine Learning Pipelines. In: ICML 2018 AutoML Workshop. ; 2018.
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2018 | Preprint | LibreCat-ID: 2711
Pauck F, Bodden E, Wehrheim H. Do Android Taint Analysis Tools Keep their Promises? arXiv:180402903. 2018.
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2018 | Preprint | LibreCat-ID: 1165
Witschen LM, Wiersema T, Platzner M. Making the Case for Proof-carrying Approximate Circuits. 4th Workshop On Approximate Computing (WAPCO 2018). 2018.
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2018 | Conference Paper | LibreCat-ID: 2109 |
Wever MD, Mohr F, Hüllermeier E. Ensembles of Evolved Nested Dichotomies for Classification. In: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018. Kyoto, Japan: ACM; 2018. doi:10.1145/3205455.3205562
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2018 | Preprint | LibreCat-ID: 17713 |
Wever MD, Mohr F, Hüllermeier E. Automated Multi-Label Classification based on ML-Plan. Published online 2018.
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2018 | Preprint | LibreCat-ID: 17714 |
Mohr F, Wever MD, Hüllermeier E. Automated machine learning service composition. Published online 2018.
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2018 | Book Chapter | LibreCat-ID: 2322
Bäumer FS, Geierhos M. How to Deal with Inaccurate Service Descriptions in On-The-Fly Computing: Open Challenges. In: Silberztein M, Atigui F, Kornyshova E, Métais E, Meziane F, eds. Proceedings of the 23rd International Conference on Natural Language and Information Systems. Vol 10859. Lecture Notes in Computer Science. Cham, Switzerland: Springer; 2018:509-513. doi:10.1007/978-3-319-91947-8_53
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2018 | Journal Article | LibreCat-ID: 2331
Kim Y, Lee S, Dollmann M, Geierhos M. Improving Classifiers for Semantic Annotation of Software Requirements with Elaborate Syntactic Structure. International Journal of Advanced Science and Technology. 2018;112:123-136. doi:10.14257/ijast.2018.112.12
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2018 | Bachelorsthesis | LibreCat-ID: 5693
Graf H. Ranking of Classification Algorithms in AutoML. Universität Paderborn; 2018.
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2018 | Conference Paper | LibreCat-ID: 5774
Töws M, Wehrheim H. Information Flow Certificates. In: Theoretical Aspects of Computing – ICTAC 2018. Cham: Springer International Publishing; 2018:435-454. doi:10.1007/978-3-030-02508-3_23
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2018 | Bachelorsthesis | LibreCat-ID: 5936
Scheibl M. Learning about Learning Curves from Dataset Properties. Universität Paderborn; 2018.
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2018 | Book Chapter | LibreCat-ID: 6423
Schäfer D, Hüllermeier E. Preference-Based Reinforcement Learning Using Dyad Ranking. In: Discovery Science. Cham: Springer International Publishing; 2018:161-175. doi:10.1007/978-3-030-01771-2_11
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