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367 Publications
2018 | Bachelorsthesis | LibreCat-ID: 3320
Rautenberg, K. (2018). Korrektheitsbeweise für Muster von Servicekompositionen. Universität Paderborn.
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2018 | Conference Paper | LibreCat-ID: 3373
Hansmeier, T., Platzner, M., & Andrews, D. (2018). An FPGA/HMC-Based Accelerator for Resolution Proof Checking. In ARC 2018: Applied Reconfigurable Computing. Architectures, Tools, and Applications (Vol. 10824, pp. 153–165). Santorini, Greece: Springer International Publishing. https://doi.org/10.1007/978-3-319-78890-6_13
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2018 | Journal Article | LibreCat-ID: 3402
Melnikov, V., & Hüllermeier, E. (2018). On the effectiveness of heuristics for learning nested dichotomies: an empirical analysis. Machine Learning. https://doi.org/10.1007/s10994-018-5733-1
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2018 | Conference Paper | LibreCat-ID: 3414
Börding, P., Haltermann, J. F., Jakobs, M.-C., & Wehrheim, H. (2018). JMCTest: Automatically Testing Inter-Method Contracts in Java. In Proceedings of the IFIP International Conference on Testing Software and Systems (ICTSS 2018) (Vol. 11146, pp. 39--55). Cádiz, Spain: Springer.
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2018 | Journal Article | LibreCat-ID: 3510 | 
Mohr, F., Wever, M. D., & Hüllermeier, E. (2018). ML-Plan: Automated Machine Learning via Hierarchical Planning. Machine Learning, 1495–1515. https://doi.org/10.1007/s10994-018-5735-z
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2018 | Conference Paper | LibreCat-ID: 3552 |
Mohr, F., Wever, M. D., & Hüllermeier, E. (n.d.). Reduction Stumps for Multi-Class Classification. In Proceedings of the Symposium on Intelligent Data Analysis. ‘s-Hertogenbosch, the Netherlands. https://doi.org/10.1007/978-3-030-01768-2_19
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2018 | Preprint | LibreCat-ID: 3586
Witschen, L. M., Wiersema, T., Ghasemzadeh Mohammadi, H., Awais, M., & Platzner, M. (n.d.). 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. (2018). FPGA-based Reconfigurable Cache Mapping Schemes: Design and Optimization. Universität Paderborn. https://doi.org/10.17619/UNIPB/1-376
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2018 | Conference Paper | LibreCat-ID: 3852 |
Wever, M. D., Mohr, F., & Hüllermeier, E. (2018). ML-Plan for Unlimited-Length Machine Learning Pipelines. In ICML 2018 AutoML Workshop. Stockholm, Sweden.
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2018 | Preprint | LibreCat-ID: 2711
Pauck, F., Bodden, E., & Wehrheim, H. (2018). Do Android Taint Analysis Tools Keep their Promises? ArXiv:1804.02903.
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2018 | Preprint | LibreCat-ID: 1165
Witschen, L. M., Wiersema, T., & Platzner, M. (2018). Making the Case for Proof-carrying Approximate Circuits. 4th Workshop On Approximate Computing (WAPCO 2018).
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2018 | Conference Paper | LibreCat-ID: 2109 |
Wever, M. D., Mohr, F., & Hüllermeier, E. (2018). 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. https://doi.org/10.1145/3205455.3205562
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2018 | Preprint | LibreCat-ID: 17713 |
Wever, M. D., Mohr, F., & Hüllermeier, E. (2018). Automated Multi-Label Classification based on ML-Plan. Arxiv.
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2018 | Preprint | LibreCat-ID: 17714 |
Mohr, F., Wever, M. D., & Hüllermeier, E. (2018). Automated machine learning service composition.
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2018 | Book Chapter | LibreCat-ID: 2322
Bäumer, F. S., & Geierhos, M. (2018). How to Deal with Inaccurate Service Descriptions in On-The-Fly Computing: Open Challenges. In M. Silberztein, F. Atigui, E. Kornyshova, E. Métais, & F. Meziane (Eds.), Proceedings of the 23rd International Conference on Natural Language and Information Systems (Vol. 10859, pp. 509–513). Cham, Switzerland: Springer. https://doi.org/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. (2018). Improving Classifiers for Semantic Annotation of Software Requirements with Elaborate Syntactic Structure. International Journal of Advanced Science and Technology, 112, 123–136. https://doi.org/10.14257/ijast.2018.112.12
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2018 | Bachelorsthesis | LibreCat-ID: 5693
Graf, H. (2018). Ranking of Classification Algorithms in AutoML. Universität Paderborn.
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2018 | Conference Paper | LibreCat-ID: 5774
Töws, M., & Wehrheim, H. (2018). Information Flow Certificates. In Theoretical Aspects of Computing – ICTAC 2018 (pp. 435–454). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-02508-3_23
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2018 | Bachelorsthesis | LibreCat-ID: 5936
Scheibl, M. (2018). Learning about learning curves from dataset properties. Universität Paderborn.
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2018 | Book Chapter | LibreCat-ID: 6423
Schäfer, D., & Hüllermeier, E. (2018). Preference-Based Reinforcement Learning Using Dyad Ranking. In Discovery Science (pp. 161–175). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-01771-2_11
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