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Eyke Hüllermeier
2010 – today
- 2013
[j66]Dominik Heider, Robin Senge, Weiwei Cheng, Eyke Hüllermeier: Multilabel classification for exploiting cross-resistance information in HIV-1 drug resistance prediction. Bioinformatics 29(16): 1946-1952 (2013)- [j65]Ammar Shaker, Robin Senge, Eyke Hüllermeier: Evolving fuzzy pattern trees for binary classification on data streams. Inf. Sci. 220: 34-45 (2013)
- [j64]Eyke Hüllermeier, Johannes Fürnkranz: Editorial: Preference learning and ranking. Machine Learning 93(2-3): 185-189 (2013)
- [j63]Thomas Fober, Marco Mernberger, Gerhard Klebe, Eyke Hüllermeier: Graph-based methods for protein structure comparison. Wiley Interdisc. Rew.: Data Mining and Knowledge Discovery 3(5): 307-320 (2013)
- [c84]Amira Abdel-Aziz, Weiwei Cheng, Marc Strickert, Eyke Hüllermeier: Preference-Based CBR: A Search-Based Problem Solving Framework. ICCBR 2013: 1-14
- [c83]Eyke Hüllermeier, Weiwei Cheng: Preference-Based CBR: General Ideas and Basic Principles. IJCAI 2013
- [p4]Thomas Fober, Gerhard Klebe, Eyke Hüllermeier: Local Clique Merging: An Extension of the Maximum Common Subgraph Measure with Applications in Structural Bioinformatics. Algorithms from and for Nature and Life 2013: 279-286
- [e5]Johannes Fürnkranz, Eyke Hüllermeier, Tomoyuki Higuchi (Eds.): Discovery Science - 16th International Conference, DS 2013, Singapore, October 6-9, 2013. Proceedings. Lecture Notes in Computer Science 8140, Springer 2013, ISBN 978-3-642-40896-0
- [i2]Eyke Hüllermeier: Learning from Imprecise and Fuzzy Observations: Data Disambiguation through Generalized Loss Minimization. CoRR abs/1305.0698 (2013)
- 2012
- [j62]Frank Hoffmann, Eyke Hüllermeier, Andreas Kroll: Ausgewählte Beiträge des GMA-Fachausschusses 5.14 "Computational Intelligence". Automatisierungstechnik 60(10): 587-588 (2012)
- [j61]Robin Senge, Thomas Fober, Maryam Nasiri, Eyke Hüllermeier: Fuzzy Pattern Trees: Ein alternativer Ansatz zur Fuzzy-Modellierung. Automatisierungstechnik 60(10): 622-629 (2012)
- [j60]Ammar Shaker, Eyke Hüllermeier: IBLStreams: a system for instance-based classification and regression on data streams. Evolving Systems 3(4): 235-249 (2012)
- [j59]M. Dolores Ruiz, Eyke Hüllermeier: A formal and empirical analysis of the fuzzy gamma rank correlation coefficient. Inf. Sci. 206: 1-17 (2012)
- [j58]Krzysztof Dembczynski, Willem Waegeman, Weiwei Cheng, Eyke Hüllermeier: On label dependence and loss minimization in multi-label classification. Machine Learning 88(1-2): 5-45 (2012)
- [j57]Johannes Fürnkranz, Eyke Hüllermeier, Weiwei Cheng, Sang-Hyeun Park: Preference-based reinforcement learning: a formal framework and a policy iteration algorithm. Machine Learning 89(1-2): 123-156 (2012)
- [j56]Ali Fallah Tehrani, Weiwei Cheng, Krzysztof Dembczynski, Eyke Hüllermeier: Learning monotone nonlinear models using the Choquet integral. Machine Learning 89(1-2): 183-211 (2012)
- [j55]Martin Pyka, A. Balz, A. Jansen, A. Krug, Eyke Hüllermeier: A WEKA Interface for fMRI Data. Neuroinformatics 10(4): 409-413 (2012)
- [j54]Humberto Bustince Sola, Miguel Pagola, Radko Mesiar, Eyke Hüllermeier, Francisco Herrera: Grouping, Overlap, and Generalized Bientropic Functions for Fuzzy Modeling of Pairwise Comparisons. IEEE T. Fuzzy Systems 20(3): 405-415 (2012)
- [j53]Eyke Hüllermeier, Maria Rifqi, Sascha Henzgen, Robin Senge: Comparing Fuzzy Partitions: A Generalization of the Rand Index and Related Measures. IEEE T. Fuzzy Systems 20(3): 546-556 (2012)
- [j52]Ali Fallah Tehrani, Weiwei Cheng, Eyke Hüllermeier: Preference Learning Using the Choquet Integral: The Case of Multipartite Ranking. IEEE T. Fuzzy Systems 20(6): 1102-1113 (2012)
- [c82]Krzysztof Dembczynski, Willem Waegeman, Eyke Hüllermeier: An Analysis of Chaining in Multi-Label Classification. ECAI 2012: 294-299
- [c81]Krzysztof Dembczynski, Wojciech Kotlowski, Eyke Hüllermeier: Consistent Multilabel Ranking through Univariate Losses. ICML 2012
- [c80]Eyke Hüllermeier, Ali Fallah Tehrani: On the VC-Dimension of the Choquet Integral. IPMU (1) 2012: 42-50
- [c79]Weiwei Cheng, Eyke Hüllermeier, Willem Waegeman, Volkmar Welker: Label Ranking with Partial Abstention based on Thresholded Probabilistic Models. NIPS 2012: 2510-2518
- [c78]Weiwei Cheng, Eyke Hüllermeier: Probability Estimation for Multi-class Classification Based on Label Ranking. ECML/PKDD (2) 2012: 83-98
- [c77]Weiwei Cheng, Krzysztof Dembczynski, Eyke Hüllermeier, Adrian Jaroszewicz, Willem Waegeman: F-Measure Maximization in Topical Classification. RSCTC 2012: 439-446
- [p3]Eyke Hüllermeier: Fuzzy Rules in Data Mining: From Fuzzy Associations to Gradual Dependencies. Combining Experimentation and Theory 2012: 123-135
- [e4]Eyke Hüllermeier, Sebastian Link, Thomas Fober, Bernhard Seeger (Eds.): Scalable Uncertainty Management - 6th International Conference, SUM 2012, Marburg, Germany, September 17-19, 2012. Proceedings. Lecture Notes in Computer Science 7520, Springer 2012, ISBN 978-3-642-33361-3
- 2011
- [j51]Carmel Domshlak, Eyke Hüllermeier, Souhila Kaci, Henri Prade: Preferences in AI: An overview. Artif. Intell. 175(7-8): 1037-1052 (2011)
- [j50]Eyke Hüllermeier: Fuzzy sets in machine learning and data mining. Appl. Soft Comput. 11(2): 1493-1505 (2011)
- [j49]Marco Mernberger, Gerhard Klebe, Eyke Hüllermeier: SEGA: Semiglobal Graph Alignment for Structure-Based Protein Comparison. IEEE/ACM Trans. Comput. Biology Bioinform. 8(5): 1330-1343 (2011)
- [j48]Thomas Fober, Gerghei Glinca, Gerhard Klebe, Eyke Hüllermeier: Superposition and Alignment of Labeled Point Clouds. IEEE/ACM Trans. Comput. Biology Bioinform. 8(6): 1653-1666 (2011)
- [j47]Robin Senge, Eyke Hüllermeier: Top-Down Induction of Fuzzy Pattern Trees. IEEE T. Fuzzy Systems 19(2): 241-252 (2011)
- [j46]Eyke Hüllermeier: Fuzzy machine learning and data mining. Wiley Interdisc. Rew.: Data Mining and Knowledge Discovery 1(4): 269-283 (2011)
- [c76]
- [c75]
- [c74]Eyke Hüllermeier, Patrice Schlegel: Preference-Based CBR: First Steps toward a Methodological Framework. ICCBR 2011: 77-91
- [c73]Wojciech Kotlowski, Krzysztof Dembczynski, Eyke Hüllermeier: Bipartite Ranking through Minimization of Univariate Loss. ICML 2011: 1113-1120
- [c72]Krzysztof Dembczynski, Willem Waegeman, Weiwei Cheng, Eyke Hüllermeier: An Exact Algorithm for F-Measure Maximization. NIPS 2011: 1404-1412
- [c71]Weiwei Cheng, Johannes Fürnkranz, Eyke Hüllermeier, Sang-Hyeun Park: Preference-Based Policy Iteration: Leveraging Preference Learning for Reinforcement Learning. ECML/PKDD (1) 2011: 312-327
- [c70]Ali Fallah Tehrani, Weiwei Cheng, Krzysztof Dembczynski, Eyke Hüllermeier: Learning Monotone Nonlinear Models Using the Choquet Integral. ECML/PKDD (3) 2011: 414-429
- [i1]Weiwei Cheng, Eyke Hüllermeier: Label Ranking with Abstention: Predicting Partial Orders by Thresholding Probability Distributions (Extended Abstract). CoRR abs/1112.0508 (2011)
- 2010
- [j45]Eyke Hüllermeier, Johannes Fürnkranz: On predictive accuracy and risk minimization in pairwise label ranking. J. Comput. Syst. Sci. 76(1): 49-62 (2010)
- [j44]Eyke Hüllermeier, Stijn Vanderlooy: Combining predictions in pairwise classification: An optimal adaptive voting strategy and its relation to weighted voting. Pattern Recognition 43(1): 128-142 (2010)
- [c69]Thomas Fober, Eyke Hüllermeier: Similarity measures for protein structures based on fuzzy histogram comparison. FUZZ-IEEE 2010: 1-7
- [c68]Robin Senge, Eyke Hüllermeier: Pattern trees for regression and fuzzy systems modeling. FUZZ-IEEE 2010: 1-7
- [c67]Thomas Fober, Marco Mernberger, Gerhard Klebe, Eyke Hüllermeier: Efficient Similarity Retrieval of Protein Binding Sites based on Histogram Comparison. GCB 2010: 51-59
- [c66]Weiwei Cheng, Krzysztof Dembczynski, Eyke Hüllermeier: Label Ranking Methods based on the Plackett-Luce Model. ICML 2010: 215-222
- [c65]Weiwei Cheng, Krzysztof Dembczynski, Eyke Hüllermeier: Graded Multilabel Classification: The Ordinal Case. ICML 2010: 223-230
- [c64]Krzysztof Dembczynski, Weiwei Cheng, Eyke Hüllermeier: Bayes Optimal Multilabel Classification via Probabilistic Classifier Chains. ICML 2010: 279-286
- [c63]Weiwei Cheng, Michaël Rademaker, Bernard De Baets, Eyke Hüllermeier: Predicting Partial Orders: Ranking with Abstention. ECML/PKDD (1) 2010: 215-230
- [c62]Krzysztof Dembczynski, Willem Waegeman, Weiwei Cheng, Eyke Hüllermeier: Regret Analysis for Performance Metrics in Multi-Label Classification: The Case of Hamming and Subset Zero-One Loss. ECML/PKDD (1) 2010: 280-295
- [c61]
- [p2]Jens Christian Hühn, Eyke Hüllermeier: An Analysis of the FURIA Algorithm for Fuzzy Rule Induction. Advances in Machine Learning I 2010: 321-344
- [e3]Eyke Hüllermeier, Rudolf Kruse, Frank Hoffmann (Eds.): Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Methods - 13th International Conference, IPMU 2010, Dortmund, Germany, June 28 - July 2, 2010. Proceedings, Part I. Communications in Computer and Information Science 80, Springer 2010, ISBN 978-3-642-14054-9
- [e2]Eyke Hüllermeier, Rudolf Kruse, Frank Hoffmann (Eds.): Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications - 13th International Conference, IPMU 2010, Dortmund, Germany, June 28 - July 2, 2010. Proceedings, Part II. Communications in Computer and Information Science 81, Springer 2010, ISBN 978-3-642-14057-0
- [e1]Eyke Hüllermeier, Rudolf Kruse, Frank Hoffmann (Eds.): Computational Intelligence for Knowledge-Based Systems Design, 13th International Conference on Information Processing and Management of Uncertainty, IPMU 2010, Dortmund, Germany, June 28 - July 2, 2010. Proceedings. Lecture Notes in Computer Science 6178, Springer 2010, ISBN 978-3-642-14048-8
- [r2]Johannes Fürnkranz, Eyke Hüllermeier: Preference Learning. Encyclopedia of Machine Learning 2010: 789-795
2000 – 2009
- 2009
- [j43]Thomas Fober, Marco Mernberger, Gerhard Klebe, Eyke Hüllermeier: Evolutionary construction of multiple graph alignments for the structural analysis of biomolecules. Bioinformatics 25(16): 2110-2117 (2009)
- [j42]Jens Christian Hühn, Eyke Hüllermeier: FURIA: an algorithm for unordered fuzzy rule induction. Data Min. Knowl. Discov. 19(3): 293-319 (2009)
- [j41]Eyke Hüllermeier, Michael M. Richter, Rosina Weber: Prelude to the papers "Fuzzy case based reasoning for facial expression recognition" and "Temporal similarity by measuring possibilistic uncertainty in CBR". Fuzzy Sets and Systems 160(2): 212-213 (2009)
- [j40]Yu Yi, Thomas Fober, Eyke Hüllermeier: Fuzzy Operator Trees for Modeling Rating Functions. International Journal of Computational Intelligence and Applications 8(4): 413-428 (2009)
- [j39]Eyke Hüllermeier, Ilya Vladimirskiy, Belén Prados-Suárez, Eva Stauch: Supporting Case-Based Retrieval by Similarity Skyline. KI 23(1): 24-29 (2009)
- [j38]Weiwei Cheng, Eyke Hüllermeier: Combining instance-based learning and logistic regression for multilabel classification. Machine Learning 76(2-3): 211-225 (2009)
- [j37]Jens C. Huhn, Eyke Hüllermeier: FR3: A Fuzzy Rule Learner for Inducing Reliable Classifiers. IEEE T. Fuzzy Systems 17(1): 138-149 (2009)
- [j36]Eyke Hüllermeier, Stijn Vanderlooy: Why Fuzzy Decision Trees are Good Rankers. IEEE T. Fuzzy Systems 17(6): 1233-1244 (2009)
- [c60]Eyke Hüllermeier, Maria Rifqi: A Fuzzy Variant of the Rand Index for Comparing Clustering Structures. IFSA/EUSFLAT Conf. 2009: 1294-1298
- [c59]Thomas Fober, Eyke Hüllermeier: Fuzzy Modeling of Labeled Point Cloud Superposition for the Comparison of Protein Binding Sites. IFSA/EUSFLAT Conf. 2009: 1299-1304
- [c58]Thomas Fober, Marco Mernberger, Ralph Moritz, Eyke Hüllermeier: Graph-Kernels for the Comparative Analysis of Protein Active Sites. GCB 2009: 21-31
- [c57]Weiwei Cheng, Jens C. Huhn, Eyke Hüllermeier: Decision tree and instance-based learning for label ranking. ICML 2009: 21
- [c56]Imen Boukhris, Zied Elouedi, Thomas Fober, Marco Mernberger, Eyke Hüllermeier: Similarity Analysis of Protein Binding Sites: A Generalization of the Maximum Common Subgraph Measure Based on Quasi-Clique Detection. ISDA 2009: 1245-1250
- [c55]Thomas Fober, Gerhard Klebe, Eyke Hüllermeier: Efficient Construction of Multiple Geometrical Alignments for the Comparison of Protein Binding Sites. ISDA 2009: 1251-1256
- [c54]Weiwei Cheng, Eyke Hüllermeier: A New Instance-Based Label Ranking Approach Using the Mallows Model. ISNN (1) 2009: 707-716
- [c53]Weiwei Cheng, Eyke Hüllermeier: Combining Instance-Based Learning and Logistic Regression for Multilabel Classification. ECML/PKDD (1) 2009: 6
- [c52]Johannes Fürnkranz, Eyke Hüllermeier, Stijn Vanderlooy: Binary Decomposition Methods for Multipartite Ranking. ECML/PKDD (1) 2009: 359-374
- [r1]Eyke Hüllermeier: Fuzzy Methods in Data Mining. Encyclopedia of Data Warehousing and Mining 2009: 907-912
- 2008
- [j35]Eyke Hüllermeier, Johannes Fürnkranz, Weiwei Cheng, Klaus Brinker: Label ranking by learning pairwise preferences. Artif. Intell. 172(16-17): 1897-1916 (2008)
- [j34]Eyke Hüllermeier, Klaus Brinker: Learning valued preference structures for solving classification problems. Fuzzy Sets and Systems 159(18): 2337-2352 (2008)
- [j33]Jens C. Huhn, Eyke Hüllermeier: Is an ordinal class structure useful in classifier learning? IJDMMM 1(1): 45-67 (2008)
- [j32]Jürgen Beringer, Eyke Hüllermeier: Case-based learning in a bipolar possibilistic framework. Int. J. Intell. Syst. 23(10): 1119-1134 (2008)
- [j31]Stijn Vanderlooy, Eyke Hüllermeier: A critical analysis of variants of the AUC. Machine Learning 72(3): 247-262 (2008)
- [j30]Johannes Fürnkranz, Eyke Hüllermeier, Eneldo Loza Mencía, Klaus Brinker: Multilabel classification via calibrated label ranking. Machine Learning 73(2): 133-153 (2008)
- [c51]Eyke Hüllermeier, Michael M. Richter, Rosina Weber, Kerstin Bach, Miltos Petridis: Preface: Uncertainty, Similarity, and Knowledge Discovery in CBR. ECCBR Workshops 2008: 117-118
- [c50]Weiwei Cheng, Eyke Hüllermeier: Learning Similarity Functions from Qualitative Feedback. ECCBR 2008: 120-134
- [c49]Weiwei Cheng, Eyke Hüllermeier: Instance-Based Label Ranking using the Mallows Model. ECCBR Workshops 2008: 143-157
- [c48]Eyke Hüllermeier, Ilya Vladimirskiy, Belén Prados-Suárez, Eva Stauch: Supporting Case-Based Retrieval by Similarity Skylines: Basic Concepts and Extensions. ECCBR 2008: 240-254
- [c47]Thomas Fober, Eyke Hüllermeier, Marco Mernberger: Evolutionary Construction of Multiple Graph Alignments for the Structural Analysis of Biomolecules. German Conference on Bioinformatics 2008: 44-53
- [c46]Thomas Fober, Eyke Hüllermeier, Marco Mernberger: Evolutionary Construction of Multiple Graph Alignments for Mining Structured Biomolecular Data. LWA 2008: 27-33
- [c45]Eyke Hüllermeier, Stijn Vanderlooy: Weighted Voting as Approximate MAP Prediction in Pairwise Classification. LWA 2008: 34-41
- [c44]Stijn Vanderlooy, Eyke Hüllermeier: A Critical Analysis of Variants of the AUC. ECML/PKDD (1) 2008: 13
- [p1]Eyke Hüllermeier: Fuzzy Methods for Data Mining and Machine Learning: State ofthe Art and Prospects. Fuzzy Sets and Their Extensions: Representation, Aggregation and Models 2008: 357-375
- 2007
- [b1]Eyke Hüllermeier: Case-Based Approximate Reasoning. Theory and Decision Library 44, Springer 2007, ISBN 978-1-4020-5694-9
- [j29]Iman Karimi, Eyke Hüllermeier: Risk assessment system of natural hazards: A new approach based on fuzzy probability. Fuzzy Sets and Systems 158(9): 987-999 (2007)
- [j28]Jürgen Beringer, Eyke Hüllermeier: Efficient instance-based learning on data streams. Intell. Data Anal. 11(6): 627-650 (2007)
- [j27]Didier Dubois, Eyke Hüllermeier: Comparing probability measures using possibility theory: A notion of relative peakedness. Int. J. Approx. Reasoning 45(2): 364-385 (2007)
- [j26]Eyke Hüllermeier, Frank Klawonn, Andreas Nürnberger: Editorial. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 15(5) (2007)
- [j25]Iman Karimi, Eyke Hüllermeier, Konstantin Meskouris: A fuzzy-probabilistic earthquake risk assessment system. Soft Comput. 11(3): 229-238 (2007)
- [j24]Ulrich Bodenhofer, Eyke Hüllermeier, Frank Klawonn, Rudolf Kruse: Special Issue on Soft Computing for Information Mining. Soft Comput. 11(5): 397-399 (2007)
- [j23]Nils Weskamp, Eyke Hüllermeier, Daniel Kuhn, Gerhard Klebe: Multiple Graph Alignment for the Structural Analysis of Protein Active Sites. IEEE/ACM Trans. Comput. Biology Bioinform. 4(2): 310-320 (2007)
- [j22]Eyke Hüllermeier: Credible Case-Based Inference Using Similarity Profiles. IEEE Trans. Knowl. Data Eng. 19(6): 847-858 (2007)
- [j21]Eyke Hüllermeier, Y. Yi: In Defense of Fuzzy Association Analysis. IEEE Transactions on Systems, Man, and Cybernetics, Part B 37(4): 1039-1043 (2007)
- [c43]Jan-Nikolas Sulzmann, Johannes Fürnkranz, Eyke Hüllermeier: On Pairwise Naive Bayes Classifiers. ECML 2007: 371-381
- [c42]Eyke Hüllermeier, Johannes Fürnkranz: On Minimizing the Position Error in Label Ranking. ECML 2007: 583-590
- [c41]Eyke Hüllermeier, Klaus Brinker: Fuzzy-Relational Classification: Combining Pairwise Decomposition Techniques with Fuzzy Preference Modeling. EUSFLAT Conf. (1) 2007: 353-360
- [c40]Jürgen Beringer, Eyke Hüllermeier: Adaptive Optimization of the Number of Clusters in Fuzzy Clustering. FUZZ-IEEE 2007: 1-6
- [c39]Eyke Hüllermeier, Nils Weskamp, Gerhard Klebe, Daniel Kuhn: Graph Alignment: Fuzzy Pattern Mining for the Structural Analysis of Protein Active Sites. FUZZ-IEEE 2007: 1-6
- [c38]
- [c37]
- [c36]Jürgen Beringer, Eyke Hüllermeier: An Efficient Algorithm for Instance-Based Learning on Data Streams. Industrial Conference on Data Mining 2007: 34-48
- [c35]Weiwei Cheng, Eyke Hüllermeier, Bernhard Seeger, Ilya Vladimirskiy: Interactive Ranking of Skylines Using Machine Learning Techniques. LWA 2007: 141-148
- 2006
- [j20]Didier Dubois, Eyke Hüllermeier, Henri Prade: A systematic approach to the assessment of fuzzy association rules. Data Min. Knowl. Discov. 13(2): 167-192 (2006)
- [j19]Jürgen Beringer, Eyke Hüllermeier: Online clustering of parallel data streams. Data Knowl. Eng. 58(2): 180-204 (2006)
- [j18]Eyke Hüllermeier, Jürgen Beringer: Learning from ambiguously labeled examples. Intell. Data Anal. 10(5): 419-439 (2006)
- [j17]Didier Dubois, Eyke Hüllermeier, Henri Prade: Fuzzy methods for case-based recommendation and decision support. J. Intell. Inf. Syst. 27(2): 95-115 (2006)
- [c34]Klaus Brinker, Johannes Fürnkranz, Eyke Hüllermeier: A Unified Model for Multilabel Classification and Ranking. ECAI 2006: 489-493
- [c33]
- [c32]Korinna Bade, Eyke Hüllermeier, Andreas Nürnberger: Hierarchical Classification by Expected Utility Maximization. ICDM 2006: 43-52
- 2005
- [j16]Rajarajeswari Balasubramaniyan, Eyke Hüllermeier, Nils Weskamp, Jörg Kämper: Clustering of gene expression data using a local shape-based similarity measure. Bioinformatics 21(7): 1069-1077 (2005)
- [j15]Eyke Hüllermeier: Special issue on fuzzy sets in knowledge discovery. Fuzzy Sets and Systems 149(1): 1-3 (2005)
- [j14]Eyke Hüllermeier: Fuzzy methods in machine learning and data mining: Status and prospects. Fuzzy Sets and Systems 156(3): 387-406 (2005)
- [j13]
- [j12]Eyke Hüllermeier: Experience-Based Decision Making: A Satisficing Decision Tree Approach. IEEE Transactions on Systems, Man, and Cybernetics, Part A 35(5): 641-653 (2005)
- [c31]Didier Dubois, Eyke Hüllermeier: A Notion of Comparative Probabilistic Entropy Based on the Possibilistic Specificity Ordering. ECSQARU 2005: 848-859
- [c30]Edwin Lughofer, Eyke Hüllermeier, Erich-Peter Klement: Improving the interpretability of data-driven evolving fuzzy systems. EUSFLAT Conf. 2005: 28-33
- [c29]Yu Yi, Eyke Hüllermeier: Learning Complexity-Bounded Rule-Based Classifiers by Combining. Association Analysis and Genetic Algorithms. EUSFLAT Conf. 2005: 47-52
- [c28]
- [c27]Eyke Hüllermeier, Johannes Fürnkranz: Learning Label Preferences: Ranking Error Versus Position Error. IDA 2005: 180-191
- [c26]Eyke Hüllermeier: Cho-k-NN: A Method for Combining Interacting Pieces of Evidence in Case-Based Learning. IJCAI 2005: 3-8
- [c25]Eyke Hüllermeier, Johannes Fürnkranz, Jürgen Beringer: On Position Error and Label Ranking through Iterated Choice. LWA 2005: 158-163
- 2004
- [j11]Nils Weskamp, Daniel Kuhn, Eyke Hüllermeier, Gerhard Klebe: Efficient similarity search in protein structure databases by k-clique hashing. Bioinformatics 20(10): 1522-1526 (2004)
- [j10]Eyke Hüllermeier: Flexible constraints for regularization in learning from data. Int. J. Intell. Syst. 19(6): 525-541 (2004)
- [j9]
- [c24]
- [c23]
- [c22]Nils Weskamp, Eyke Hüllermeier, Daniel Kuhn, Gerhard Klebe: Graph Alignments: A New Concept to Detect Conserved Regions in Protein Active Sites. German Conference on Bioinformatics 2004: 131-140
- 2003
- [j8]
- [j7]Martine de Calmès, Didier Dubois, Eyke Hüllermeier, Henri Prade, Florence Sedes: Flexibility and Fuzzy Case-Based Evaluation in Querying: An Illustration in an Experimental Setting. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 11(1): 43-66 (2003)
- [j6]Didier Dubois, Eyke Hüllermeier, Henri Prade: On the representation of fuzzy rules in terms of crisp rules. Inf. Sci. 151: 301-326 (2003)
- [c21]
- [c20]Eyke Hüllermeier: Instance-based collaborative filtering with fuzzy labels. EUSFLAT Conf. 2003: 468-473
- [c19]Nils Weskamp, Daniel Kuhn, Eyke Hüllermeier, Gerhard Klebe: Efficient Similarity Search in Protein Structure Databases: Improving Cliqae-Detection through Clique Hashing. German Conference on Bioinformatics 2003: 179-184
- [c18]
- [c17]Didier Dubois, Eyke Hüllermeier, Henri Prade: A Note on Quality Measures for Fuzzy Asscociation Rules. IFSA 2003: 346-353
- [c16]Eyke Hüllermeier: Inducing Fuzzy Concepts through Extended Version Space Learning. IFSA 2003: 677-684
- [c15]
- 2002
- [j5]Didier Dubois, Eyke Hüllermeier, Henri Prade: Fuzzy set-based methods in instance-based reasoning. IEEE T. Fuzzy Systems 10(3): 322-332 (2002)
- [j4]Eyke Hüllermeier, Didier Dubois, Henri Prade: Model adaptation in possibilistic instance-based reasoning. IEEE T. Fuzzy Systems 10(3): 333-339 (2002)
- [c14]Eyke Hüllermeier: On the Representation and Combination of Evidence in Instance-Based Learning. ECAI 2002: 360-364
- [c13]
- [c12]Martine de Calmès, Didier Dubois, Eyke Hüllermeier, Henri Prade, Florence Sedes: A Fuzzy Approach to Flexible Case-based Querying: Methodology and Experimentation. KR 2002: 449-458
- [c11]
- 2001
- [j3]Eyke Hüllermeier: Similarity-based inference as evidential reasoning. Int. J. Approx. Reasoning 26(2): 67-100 (2001)
- [c10]Eyke Hüllermeier: Fuzzy Association Rules: Semantic Issues and Quality Measures. Fuzzy Days 2001: 380-391
- [c9]
- 2000
- [c8]
- [c7]
- [c6]
- [c5]Didier Dubois, Eyke Hüllermeier, Henri Prade: Flexible Control of Case-Based Prediction in the Framework of Possibility Theory. EWCBR 2000: 61-73
- [c4]Eyke Hüllermeier: A Method for Predicting Solutions in Case-Based Problem Solving. EWCBR 2000: 124-135
1990 – 1999
- 1999
- [j2]Eyke Hüllermeier: Numerical Methods for Fuzzy Initial Value Problems. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 7(5): 439-461 (1999)
- [c3]Eyke Hüllermeier: A Possibilistic Formalization of Case-Based Reasoning and Decision Making. Fuzzy Days 1999: 411-420
- [c2]Eyke Hüllermeier: Exploiting Similarity for Supporting Data Analysis and Problem Solving. IDA 1999: 257-268
- [c1]
- 1997
- [j1]Eyke Hüllermeier: An Approach to Modelling and Simulation of Uncertain Dynamical Systems. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 5(2): 117-138 (1997)
Coauthor Index
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last updated on 2013-10-02 11:19 CEST by the dblp team