Wever, Marcel Dominik, Felix Mohr, and Eyke Hüllermeier. “Ensembles of Evolved Nested Dichotomies for Classification.”https://doi.org/10.1145/3205455.3205562__In Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2018, Kyoto, Japan, July 15-19, 2018. Kyoto, Japan: ACM, 2018.https://doi.org/10.1145/3205455.3205562 .
LibreCat: /record/2109
DOI: 10.1145/3205455.3205562

Wever, Marcel Dominik, Felix Mohr, and Eyke Hüllermeier. “Automated Multi-Label Classification Based on ML-Plan.” Arxiv, 2018.
LibreCat: /record/17713

Mohr, Felix, Marcel Dominik Wever, and Eyke Hüllermeier. “Automated Machine Learning Service Composition,” 2018.
LibreCat: /record/17714

Graf, Helena. Ranking of Classification Algorithms in AutoML. Universität Paderborn, 2018.
LibreCat: /record/5693

Scheibl, Manuel. Learning about Learning Curves from Dataset Properties. Universität Paderborn, 2018.
LibreCat: /record/5936

Schäfer, Dirk, and Eyke Hüllermeier. “Preference-Based Reinforcement Learning Using Dyad Ranking.”https://doi.org/10.1007/978-3-030-01771-2_11__In Discovery Science, 161–75. Cham: Springer International Publishing, 2018.https://doi.org/10.1007/978-3-030-01771-2_11 .
LibreCat: /record/6423
DOI: 10.1007/978-3-030-01771-2_11

Abiteboul, S., M. Arenas, P. Barceló, M. Bienvenu, D. Calvanese, C. David, R. Hull, et al., eds. Research Directions for Principles of Data Management. Vol. 7, 2018.
LibreCat: /record/10591

Couso, Ines, and Eyke Hüllermeier. “Statistical Inference for Incomplete Ranking Data: A Comparison of Two Likelihood-Based Estimators.” In Frontiers in Computational Intelligence, edited by Sanaz Mostaghim, Andreas Nürnberger, and Christian Borgelt, 31–46. Springer, 2018.
LibreCat: /record/10783

Schäfer, D., and Eyke Hüllermeier. “Dyad Ranking Using Plackett-Luce Models Based on Joint Feature Representations.” Machine Learning 107, no. 5 (2018): 903–41.
LibreCat: /record/16038

Ahmadi Fahandar, Mohsen, and Eyke Hüllermeier. “Learning to Rank Based on Analogical Reasoning.” In Proc. 32 Nd AAAI Conference on Artificial Intelligence (AAAI), 2951–58, 2018.
LibreCat: /record/10145

El Mesaoudi-Paul, Adil, Eyke Hüllermeier, and Robert Busa-Fekete. “Ranking Distributions Based on Noisy Sorting.” In Proc. 35th Int. Conference on Machine Learning (ICML), 3469–77. Verlagsschriftenreihe Des Heinz Nixdorf Instituts, Paderborn. Verlagsschriftenreihe des Heinz Nixdorf Instituts, Paderborn, 2018.
LibreCat: /record/10148

Hesse, M., J. Timmermann, Eyke Hüllermeier, and Ansgar Trächtler. “A Reinforcement Learning Strategy for the Swing-Up of the Double Pendulum on a Cart.” In Proc. 4th Int. Conference on System-Integrated Intelligence: Intelligent, Flexible and Connected Systems in Products and Production, Procedia Manufacturing 24, 15–20, 2018.
LibreCat: /record/10149

Mencia, E.Loza, J. Fürnkranz, Eyke Hüllermeier, and M. Rapp. “Learning Interpretable Rules for Multi-Label Classification.” In Explainable and Interpretable Models in Computer Vision and Machine Learning, edited by H. Jair Escalante, S. Escalera, I. Guyon, X. Baro, Y. Güclüütürk, U. Güclü, and M.A.J. van Gerven, 81–113. The Springer Series on Challenges in Machine Learning. Springer, 2018.
LibreCat: /record/10152

Nguyen, Vu-Linh, Sebastian Destercke, M.-H. Masson, and Eyke Hüllermeier. “Reliable Multi-Class Classification Based on Pairwise Epistemic and Aleatoric Uncertainty.” In Proc. 27th Int.Joint Conference on Artificial Intelligence (IJCAI), 5089–95, 2018.
LibreCat: /record/10181

Schäfer, Dirk, and Eyke Hüllermeier. “Preference-Based Reinforcement Learning Using Dyad Ranking.” In Proc. 21st Int. Conference on Discovery Science (DS), 161–75, 2018.
LibreCat: /record/10184

Schäfer, Dirk, and Eyke Hüllermeier. “Dyad Ranking Using Plackett-Luce Models Based on Joint Feature Representations.” Machine Learning 107, no. 5 (2018): 903–41.
LibreCat: /record/10276

Seemann, Nina, Michaela Geierhos, Marie-Luis Merten, Doris Tophinke, Marcel Dominik Wever, and Eyke Hüllermeier. “Supporting the Cognitive Process in Annotation Tasks.” In Postersession Computerlinguistik der 40. Jahrestagung der Deutschen Gesellschaft für Sprachwissenschaft, edited by Kerstin  Eckart and Dominik  Schlechtweg, 2018.
LibreCat: /record/1379

Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “Analysis of Gradient Descent Methods with Nondiminishing Bounded Errors.” IEEE Transactions on Automatic Control 63, no. 5 (2017): 1465–71.
LibreCat: /record/24152

Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “A Generalization of the Borkar-Meyn Theorem for Stochastic Recursive Inclusions.” Mathematics of Operations Research 42, no. 3 (2017): 648–61.
LibreCat: /record/24153

Melnikov, Vitalik, and Eyke Hüllermeier. “Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics.”https://doi.org/10.5445/KSP/1000074341__In Proceedings. 27. Workshop Computational Intelligence, Dortmund, 23. - 24. November 2017. KIT Scientific Publishing, 2017.https://doi.org/10.5445/KSP/1000074341 .
LibreCat: /record/3325
DOI: 10.5445/KSP/1000074341

Jakobs, Marie-Christine, Julia Krämer, Dirk van Straaten, and Theodor Lettmann. “Certiû01cation Matters for Service Markets.” In The Ninth International Conferences on Advanced Service Computing (SERVICE COMPUTATION), edited by Thomas Prinz Marcelo De Barros, Janusz Klink,Tadeus Uhl, 7–12, 2017.
LibreCat: /record/115

Seemann, Nina, Marie-Luis Merten, Michaela Geierhos, Doris Tophinke, and Eyke Hüllermeier. “Annotation Challenges for Reconstructing the Structural Elaboration of Middle Low German.”https://doi.org/10.18653/v1/W17-2206__In Proceedings of the Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, 40–45. Stroudsburg, PA, USA: Association for Computational Linguistics (ACL), 2017.https://doi.org/10.18653/v1/W17-2206 .
LibreCat: /record/1158
DOI: 10.18653/v1/W17-2206

Schnitker, Nino Noel. Genetischer Algorithmus zur Erstellung von Ensembles von Nested Dichotomies. Universität Paderborn, 2017.
LibreCat: /record/5694

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.
LibreCat: /record/5722

Hetzer, Alexander, and Tanja Tornede. Solving the Container Pre-Marshalling Problem Using Reinforcement Learning and Structured Output Prediction. Universität Paderborn, 2017.
LibreCat: /record/5724

Czech, Mike, Eyke Hüllermeier, Marie-Christine Jakobs, and Heike Wehrheim. “Predicting Rankings of Software Verification Tools.”https://doi.org/10.1145/3121257.3121262__In Proceedings of the 3rd International Workshop on Software Analytics, 23–26. SWAN’17, 2017.https://doi.org/10.1145/3121257.3121262 .
LibreCat: /record/71
DOI: 10.1145/3121257.3121262

Czech, Mike, Eyke Hüllermeier, Marie-Christine Jakobs, and Heike Wehrheim. Predicting Rankings of Software Verification Competitions, 2017.
LibreCat: /record/72

Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” In Encyclopedia of Machine Learning and Data Mining, 1000–1005, 2017.
LibreCat: /record/10589

Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” In Encyclopedia of Machine Learning and Data Mining, edited by C. Sammut and G.I. Webb, 107:1000–1005. Springer, 2017.
LibreCat: /record/10784

Wever, Marcel Dominik, Felix Mohr, and Eyke Hüllermeier. “Automatic Machine Learning: Hierachical Planning Versus Evolutionary Optimization.” In 27th Workshop Computational Intelligence. Dortmund, 2017.
LibreCat: /record/1180

Melnikov, Vitaly, and Eyke Hüllermeier. “Optimizing the Structure of Nested Dichotomies. A Comparison of Two Heuristics.” In In Proceedings 27th Workshop Computational Intelligence, Dortmund Germany, edited by F. Hoffmann, Eyke Hüllermeier, and R. Mikut, 1–12. KIT Scientific Publishing, 2017.
LibreCat: /record/15397

Czech, M., Eyke Hüllermeier, M.C. Jacobs, and Heike Wehrheim. “Predicting Rankings of Software Verification Tools.” In In Proceedings ESEC/FSE Workshops 2017 - 3rd ACM SIGSOFT, International Workshop on Software Analytics (SWAN 2017), Paderborn Germany, 2017.
LibreCat: /record/15399

Couso, Ines, D. Dubois, and Eyke Hüllermeier. “Maximum Likelihood Estimation and Coarse Data.” In In Proceedings SUM 2017, 11th International Conference on Scalable Uncertainty Management, Granada, Spain, 3–16. Springer, 2017.
LibreCat: /record/15110

Ewerth, Ralph, M. Springstein, E. Müller, A. Balz, J. Gehlhaar, T. Naziyok, K. Dembczynski, and Eyke Hüllermeier. “Estimating Relative Depth in Single Images via Rankboost.” In Proc. IEEE Int. Conf. on Multimedia and Expo (ICME 2017), 919–24, 2017.
LibreCat: /record/10204

Ahmadi Fahandar, Mohsen, Eyke Hüllermeier, and Ines Couso. “Statistical Inference for Incomplete Ranking Data: The Case of Rank-Dependent  Coarsening.” In Proc. 34th Int. Conf. on Machine Learning (ICML 2017), 1078–87, 2017.
LibreCat: /record/10205

Mohr, Felix, Theodor Lettmann, and Eyke Hüllermeier. “Planning with Independent Task Networks.”https://doi.org/10.1007/978-3-319-67190-1_15__In Proc. 40th Annual German Conference on Advances in Artificial Intelligence (KI 2017), 193–206, 2017.https://doi.org/10.1007/978-3-319-67190-1_15 .
LibreCat: /record/10206
DOI: 10.1007/978-3-319-67190-1_15

Czech, M., Eyke Hüllermeier, M.-C. Jakobs, and Heike Wehrheim. “Predicting Rankings of Software Verification Tools.” In Proc. 3rd ACM SIGSOFT Int. I Workshop on Software Analytics (SWAN@ESEC/SIGSOFT FSE 2017, 23–26, 2017.
LibreCat: /record/10207

Couso, Ines, D. Dubois, and Eyke Hüllermeier. “Maximum Likelihood Estimation and Coarse Data.” In Proc. 11th Int. Conf. on Scalable Uncertainty Management (SUM 2017), 3–16, 2017.
LibreCat: /record/10208

Ahmadi Fahandar, Mohsen, and Eyke Hüllermeier. “Learning to Rank Based on Analogical Reasoning.” In Proc. AAAI 2017, 32nd AAAI Conference on Artificial Intelligence, 2017.
LibreCat: /record/10209

Hoffmann, F., Eyke Hüllermeier, and R. Mikut. “(Hrsg.) Proceedings 27. Workshop Computational Intelligence, KIT Scientific Publishing, Karlsruhe, Germany 2017,” 2017.
LibreCat: /record/10212

Melnikov, Vitaly, and Eyke Hüllermeier. “Optimizing the Structure of Nested Dichotomies: A Comparison of Two Heuristics.” In Proceedings 27. Workshop Computational Intelligence, Dortmund, Germany 2017, 1–12, 2017.
LibreCat: /record/10213

Shaker, Ammar, W. Heldt, and Eyke Hüllermeier. “Learning TSK Fuzzy Rules from Data Streams.” In Proceedings ECML/PKDD, European Conference on Machine Learning and Knowledge Discovery in Databases, Skopje, Macedonia, 2017.
LibreCat: /record/10216

Bräuning, M., Eyke Hüllermeier, T. Keller, and M. Glaum. “Lexicographic Preferences for Predictive Modeling of Human Decision Making. A New Machine Learning Method with an Application  in Accounting.” European Journal of Operational Research 258, no. 1 (2017): 295–306.
LibreCat: /record/10267

Platenius, M.-C., Ammar Shaker, M. Becker, Eyke Hüllermeier, and W. Schäfer. “Imprecise Matching of Requirements Specifications for Software Services Using Fuzzy Logic.” IEEE Transactions on Software Engineering 43, no. 8 (2017): 739–59.
LibreCat: /record/10268

Hüllermeier, Eyke. “From Knowledge-Based to Data-Driven Modeling of Fuzzy Rule-Based Systems: A Critical Reflection.” The Computing Research Repository  (CoRR), 2017.
LibreCat: /record/10269

Ramaswamy, Arunselvan, and Shalabh Bhatnagar. “Stochastic Recursive Inclusion in Two Timescales with an Application to the Lagrangian Dual Problem.” Stochastics 88, no. 8 (2016): 1173–87.
LibreCat: /record/24154

Melnikov, Vitalik, Eyke Hüllermeier, Daniel Kaimann, Berndhttps://doi.org/10.4467/20838476si.16.006.6187__Frick, andhttps://doi.org/10.4467/20838476si.16.006.6187__Prithahttps://doi.org/10.4467/20838476si.16.006.6187__Gupta. “Pairwise versus Pointwise Ranking: A Case Study.”https://doi.org/10.4467/20838476si.16.006.6187__Schedae Informaticae 25 (2016).https://doi.org/10.4467/20838476si.16.006.6187 .
LibreCat: /record/3318
DOI: 10.4467/20838476si.16.006.6187

Platenius, Marie Christin, Ammar Shaker, Matthias Becker, Eyke Hüllermeier, and Wilhelm Schäfer. “Imprecise Matching of Requirements Specifications for Software Services Using Fuzzy Logic.”https://doi.org/10.1109/TSE.2016.2632115__IEEE Transactions on Software Engineering (TSE), Presented at ICSE 2017, no. 8 (2016): 739–59.https://doi.org/10.1109/TSE.2016.2632115 .
LibreCat: /record/190
DOI: 10.1109/TSE.2016.2632115

Melnikov, Vitaly, and Eyke Hüllermeier. “Learning to Aggregate Using Uninorms.”https://doi.org/10.1007/978-3-319-46227-1_47__In Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML/PKDD 2016), 756–71. LNCS, 2016.https://doi.org/10.1007/978-3-319-46227-1_47 .
LibreCat: /record/184
DOI: 10.1007/978-3-319-46227-1_47

Fürnkranz, J., and Eyke Hüllermeier. “Preference Learning.” In Encyclopedia of Machine Learning and Data Mining, edited by C. Sammut and G.I. Webb. Springer, 2016.
LibreCat: /record/10785