Keywords:
- aggregation
- Bag Classification
- binary decomposition
- Combine then Predict
- decision under risk and unce
- Denoising Autoencoder
- efficient classification
- efficient decoding
- efficient voting
- Ensembles of Multilabel Classifiers
- EUR-Lex Database
- F-measure
- fegelod
- Fusion
- Gradient boosting
- Hamming loss
- heuristics
- Label Dependencies
- learning by pairwise comparison
- Legal Documents
- machine learning
- Multi-Instance Learning
- multiclass classification
- multilabel classification
- multiple criteria decision making
- Outbreak Detection
- pairwise classification
- Predict then Combine
- preference elicitation
- Preference learning
- ranking
- Reinforcement learning
- Reproduction-Error Representation
- Rule Learning
- separate- and-conquer
- social choice
- Stacking
- Subset 0/1 loss
- Surveillance
- ternary ECOC
- Text Classification
- voting aggregation
Publications of Johannes Fürnkranz sorted by recency
| , , and , Correlation-based Discovery of Disease Patterns for Syndromic Surveillance (2021), in: Frontiers in Big Data |
| , , and , Correlation-based Discovery of Disease Patterns for Syndromic Surveillance (2021), in: CoRR, abs/2110.09208 |
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| , , and , Sum-Product Networks for Early Outbreak Detection of Emerging Diseases, in: Artificial Intelligence in Medicine, pages 61--71, Springer International Publishing, 2021 |
| , and , A Unifying Framework and Comparative Evaluation of Statistical and Machine Learning Approaches to Non-Specific Syndromic Surveillance (2021), in: Computers, 10:3 |
[DOI] [URL] |
| , and , Revisiting Non-Specific Syndromic Surveillance, in: Advances in Intelligent Data Analysis {XIX} - 19th International Symposium on Intelligent Data Analysis, {IDA} 2021, Porto, Portugal, April 26-28, 2021, Proceedings, pages 128-140, Springer International Publishing, 2021 |
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| , , and , Tree-Based Dynamic Classifier Chains (2021), in: Machine Learning Journal |
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| , , and , Gradient-Based Label Binning in Multi-Label Classification, in: Machine Learning and Knowledge Discovery in Databases (ECML-PKDD), Springer, 2021 |
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| , and , Revisiting Non-Specific Syndromic Surveillance (2021), in: CoRR, abs/2101.12246 |
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| , , and , Comparing Boosting and Bagging for Decision Trees of Rankings (2021), in: Journal of Classification |
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| , and , Conformal Rule-Based Multi-label Classification, in: KI 2020: Advances in Artificial Intelligence, Springer, Cham, 2020 |
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| , , and , Learning Structured Declarative Rule Sets — A Challenge for Deep Discrete Learning, in: 2nd Workshop on Deep Continuous-Discrete Machine Learning (DeCoDeML), 2020 |
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| , , , and , Rule-Based Multi-label Classification: Challenges and Opportunities, in: Rules and Reasoning, pages 3--19, Springer International Publishing, 2020 |
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| , , , and , Learning Gradient Boosted Multi-label Classification Rules, in: Machine Learning and Knowledge Discovery in Databases (ECML-PKDD), pages 124--140, Springer, 2020 |
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| , , , and , A Flexible Class of Dependence-sensitive Multi-label Loss Functions (2021), in: Machine Learning Journal |
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| , , and , PLAY: A Profiled Linear Weighting Scheme for Understanding the Influence of Input Variables on the Output of a Deep Artificial Neural Network (2020), in: Archives of Data Science, Series A |
| , , , and , On Aggregation in Ensembles of Multilabel Classifiers, in: Discovery Science, pages 533--547, Springer International Publishing, 2020 |
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| , and , Learning Analogy-Preserving Sentence Embeddings for Answer Selection, in: Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL), pages 910--919, Association for Computational Linguistics, 2019 |
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| , and , Simplifying Random Forests: On the Trade-off between Interpretability and Accuracy, Knowledge Engineering Group, Technische Universität Darmstadt, number 1911.04393, ArXiv e-prints, 2019 |
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| , and , Improving the Fusion of Outbreak Detection Methods with Supervised Learning, in: Computational Intelligence Methods for Bioinformatics and Biostatistics - 16th International Meeting, {CIBB} 2019, Bergamo, Italy, September 4-6, 2019, Revised Selected Papers, Bergamo, Italy, pages 55--66, Springer, 2020 |
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| , and , Improving Outbreak Detection with Stacking of Statistical Surveillance Methods, in: Workshop Proceedings of epiDAMIK: Epidemiology meets Data Mining and Knowledge discovery (held in conjunction with ACM SIGKDD 2019), Anchorage, USA, 2019 |
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| , and , On the Trade-off Between Consistency and Coverage in Multi-label Rule Learning Heuristics, Knowledge Engineering Group, Technische Universität Darmstadt, number 1908.03032, ArXiv e-prints, 2019 |
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| , and , On the Trade-off Between Consistency and Coverage in Multi-label Rule Learning Heuristics, in: Discovery Science, pages 96--111, Springer International Publishing, 2019 |
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| , and , Advances in Machine Learning for the Behavioral Sciences (2020), in: American Behavioral Scientist, 64:2(145--175) |
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| , , , , and , Learning Context-dependent Label Permutations for Multi-label Classification, in: Proceedings of the 36th International Conference on Machine Learning (ICML-19), pages 4733--4742, {PMLR}, 2019 |
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| and , Driver Information Embedding with Siamese LSTM networks, in: 2019 IEEE Intelligent Vehicles Symposium (IV), Paris, France, IEEE, 2019 |
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| , and , Beta Distribution Drift Detection for Adaptive Classifiers, in: Proceedings of the 2019 European Symposium on Artificial Neural Networks -- ESANN'19, 2019 |
| , and , Patching Deep Neural Networks for Nonstationary Environments, in: Proceedings of the 2019 International Joint Conference on Neural Networks -- IJCNN'19, 2019 |
| , and , Mending is Better than Ending: Adapting Immutable Classifiers to Nonstationary Environments using Ensembles of Patches, in: Proceedings of the 2019 International Joint Conference on Neural Networks -- IJCNN'19, 2019 |
| and , Exploiting Maneuver Dependency for Personalization of Driver Assistance Systems, in: 12. Uni-DAS e.V. Workshop Fahrerassistenz und automatisiertes Fahren. Uni-DAS, pages 106--115, 2018 |
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| and , Using Past Maneuver Executions for Personalization of a Driver Model, in: Proceedings of the 21th IEEE International Conference on Intelligent Transportation Systems (ITSC-18), Maui, Hawaii, pages 742--748, IEEE, 2018 |
| , , , , , , , , and , What’s important in a text? An extensive evaluation of linguistic annotations for summarization, in: Proceedings of the 5th International Conference on Social Networks Analysis, Management and Security (SNAMS-18), Valencia, Spain, pages 272--277, 2018 |
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| and , Exploiting Maneuver Dependency for Personalization of a Driver Model, in: Proceedings of the Conference ``Lernen, Wissen, Daten, Analysen'' ({LWDA}-18), pages 93--97, CEUR-WS.org, 2018 |
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| , and , Preference-Based Monte Carlo Tree Search, in: Proceedings of the 41st German Conference on Artficial Intelligence (KI-18), pages 327--340, Springer, 2018 |
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| , and , Towards Semi-Supervised Classification of Event Streams via Denoising Autoencoders, in: Proceedings of the 17th IEEE International Conference on Machine Learning and Applications (ICMLA-18), pages 131--136, IEEE, 2018 |
| , and , Leveraging Reproduction-Error Representations for Multi-Instance Classification, in: Proceedings of the 21st International Conference on Discovery Science - DS'18, Limassol, Cyprus, pages 83-95, Springer Nature Switzerland AG, 2018 |
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| and , The Need for Interpretability Biases, in: Proceedings of the 17th International Symposium on Intelligent Data Analysis (IDA-18), 's-Hertogenbosch, the Netherlands, pages 15--27, Springer-Verlag, 2018 |
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| , , and , Determining Factors for Slum Growth with Predictive Data Mining Methods (2018), in: Urban Science, 2:3(81:1--81:19) |
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| , , and , Learning Interpretable Rules for Multi-label Classification, in: Explainable and Interpretable Models in Computer Vision and Machine Learning, pages 81--113, Springer-Verlag, 2018 |
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| , and , Exploiting Anti-monotonicity of Multi-label Evaluation Measures for Inducing Multi-label Rules, in: PAKDD 2018: Advances in Knowledge Discovery and Data Mining, pages 29--42, Springer International Publishing, 2018 |
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| , and , On Cognitive Preferences and the Plausibility of Rule-based Models (2018), in: arXiv preprint arXiv:1803.01316 |
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| and , Batchwise Patching of Classifiers, in: Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), pages 3374--3381, 2018 |
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| , and , Which Scores to Predict in Sentence Regression for Text Summarization?, in: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT 2018), pages 1782--1791, 2018 |
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| , , and , Time-to-Lane-Change Prediction with Deep Learning, in: Proceedings of the 20th IEEE International Conference on Intelligent Transportation Systems (ITSC-17), IEEE, 2017 |
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| KI 2017: Advances in Artificial Intelligence, Springer-Verlag, 2017 |
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| , and , Re-training Deep Neural Networks to Facilitate Boolean Concept Extraction, in: Proceedings of the 20th International Conference on Discovery Science (DS-17), pages 127--143, Springer-Verlag, 2017 |
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| , and , Evaluation of Different Heuristics for Accommodating Asymmetric Loss Functions in Regression, in: Proceedings of the 20th International Conference on Discovery Science (DS-17), Kyoto, Japan, Springer-Verlag, 2017 |
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| , , and , Maximizing Subset Accuracy with Recurrent Neural Networks in Multi-label Classification, in: Advances in Neural Information Processing Systems 30 (NIPS-17), pages 5419--5429, 2017 |
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| , , , and , Informed Hybrid Game Tree Search (2018), in: IEEE Transactions on Games, 10:1(78--90) |
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| , , and , Multi-Objective Optimisation-based Feature Selection for Multi-Label Classification, Knowledge Engineeering Group, TU Darmstadt, number TUD-KE-2017-01, 2017 |
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| , , and , Multi-Objective Optimisation-based Feature Selection for Multi-Label Classification, in: Proceedings of the 22nd International Conference on Natural Language and Information Systems (NLDB-17), pages 38--41, Springer-Verlag, 2017 |
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| , , , , , and , Interactive Data Analytics for the Humanities, in: Proceedings of the 18th International Conference on Computational Linguistics and Intelligent Text Processing (CICLing-17), pages 527--549, Springer-Verlag, 2018 |
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| , , and , Refinement and Selection Heuristics in Subgroup Discovery and Classification Rule Learning (2017), in: Expert Systems with Applications, 81(147--162) |
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| , and , Sequential Clustering and Contextual Importance Measures for Incremental Update Summarization, in: Proceedings of the 26th International Conference on Computational Linguistics, Osaka, Japan, pages 1071-1082, The COLING 2016 Organizing Committee, 2016 |
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| , , and , A Survey of Preference-Based Reinforcement Learning Methods (2017), in: Journal of Machine Learning Research, 18:136(1--46) |
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| , , , and , Informed Hybrid Game Tree Search, Knowledge Engineering Group, Technische Universität Darmstadt, number TUD–KE–2016–01, 2016 |
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| , and , Predicting Cargo Train Failures: A Machine Learning Approach for a Lightweight Prototype, in: Proceedings of the 19th International Conference on Discovery Science (DS-16), Bari, Italy, pages 151--166, Springer-Verlag, 2016 |
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| and , Special Issue on Discovery Science (2016), in: Information Sciences, 329(849--850) |
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| , and , What Makes Word-level Neural Machine Translation Hard: A Case Study on English-German Translation, in: Proceedings of the 26th International Conference on Computational Linguistics (COLING-16), pages 3199--3208, ACL, 2016 |
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| , and , Shorter Rules Are Better, Aren't They?, in: Proceedings of the 19th International Conference on Discovery Science (DS-16), pages 279--294, Springer-Verlag, 2016 |
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| , and , Beyond Centrality and Structural Features: Learning Information Importance for Text Summarization, in: Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning, Berlin, Germany, pages 84-94, Association for Computational Linguistics, 2016 |
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| , , and , Using Semantic Similarity for Multi-Label Zero-Shot Classification of Text Documents, in: Proceedings of the 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN-16), d-side publications, 2016 |
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| , and , Evaluation of different Regression Learners under Asymmetric Loss for Predictive Maintenance, Knowledge Engineering Group, Technische Universität Darmstadt, number TUD–KE–2015–02, 2015 |
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| , and , Model-Free Preference-based Reinforcement Learning, in: Proceedings of the 30th {AAAI} Conference on Artificial Intelligence (AAAI-16), Phoenix, Arizona, pages 2222--2228, 2016 |
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| , and , All-in Text: Learning Document, Label, and Word Representations Jointly, in: Proceedings of the 30th AAAI Conference on Artificial Intelligence, Phoenix, Arizona, pages 1948--1954, AAAI Press, 2016 |
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| , , , , , , , , , , , and , Knowledge Discovery in Scientific Literature, in: Proceedings of the 12th Edition of the Konvens Conference, pages 66--76, Universitätsbibliothek Hildesheim, 2014 |
| and , A Brief Overview of Rule Learning, in: Rule Technologies: Foundations, Tools, and Applications -- Proceedings of the 9th International Symposium (RuleML-15), pages 54--69, Springer, 2015 |
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| , , and , Predicting Unseen Labels using Label Hierarchies in Large-Scale Multi-label Learning, in: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Porto, Portugal, pages 102-118, Springer International Publishing, 2015 |
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| , , and , Event-Based Clustering for Reducing Labeling Costs of Incident-Related Microposts, in: Proceedings of the ICML-15 2nd International Workshop on Mining Urban Data (MUD-15), Lille, France, pages 44--52, CEUR workshop proceedings, 2015 |
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| , , and , Event-Based Clustering for Reducing Labeling Costs of Event-Related Microposts, in: Proceedings of the 9th International AAAI Conference on Web and Social Media (ICWSM-15), Oxford, UK, pages 686--690, AAAI Press, 2015 |
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| and , Preference Learning from Annotated Game Databases, in: Proceedings of the 16th {LWA} Workshops: KDML, {IR} and FGWM, pages 57--68, CEUR-WS.org, 2014 |
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| and , On Learning Vector Representations in Hierarchical Label Spaces (2014), in: arXiv preprint arXiv:1412.6881 |
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| , , , and , Large-Scale Multi-label Text Classification - Revisiting Neural Networks, in: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD-14), Part 2, pages 437--452, Springer Berlin Heidelberg, 2014 |
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| , and , Graded Multilabel Classification by Pairwise Comparisons, Knowledge Engineering Group, Technische Universität Darmstadt, Technical Report, 2014 |
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| , and , Graded Multilabel Classification by Pairwise Comparisons, in: 2014 IEEE International Conference on Data Mining (ICDM 2014), pages 731--736, Curran Associates, IEEE, 2014 |
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| , and , Separating Rule Refinement and Rule Selection Heuristics in Inductive Rule Learning, in: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD-14), Part 3, pages 114--129, Springer, 2014 |
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| , , , and , Preference Learning (Dagstuhl Seminar 14101) (2014), in: Dagstuhl Reports, 4:3(1--27) |
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| and , On Learning from Game Annotations (2015), in: IEEE Transactions on Computational Intelligence and AI in Games, 7:3(304-316) |
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| and , Efficient Implementation of Class-Based Decomposition Schemes for Naive Bayes (2014), in: Machine Learning, 96:3(295--309) |
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| and , EPMC: Every Visit Preference Monte Carlo for Reinforcement Learning, in: Proceedings of the 5th Asian Conference on Machine Learning, (ACML-13), pages 483--497, JMLR.org, 2013 |
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| and , Preference-Based Reinforcement Learning: A Preliminary Survey, in: Proceedings of the ECML/PKDD-13 Workshop on Reinforcement Learning from Generalized Feedback: Beyond Numeric Rewards, 2013 |
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| Proceedings of the ECML/PKDD-13 Workshop on Reinforcement Learning with Generalized Feedback: Beyond Numeric Rewards, 2013 |
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| Special Issue on Preference Learning and Ranking (2013), in: Machine Learning, 93:2-3 |
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| and , Editorial: Preference Learning and Ranking (2013), in: Machine Learning, 93:2-3(185--189) |
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| Proceedings of the 16th International Conference on Discovery Science (DS-13), Springer-Verlag, 2013 |
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| , Rule-Based Methods, in: Encyclopedia of Systems Biology, Springer-Verlag, 2013 |
| and , A Policy Iteration Algorithm for Learning from Preference-based Feedback, in: Advances in Intelligent Data Analysis XII: 12th International Symposium (IDA-13), pages 427--437, Springer-Verlag, 2013 |
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| and , Learning from Trajectory-Based Action Preferences, in: Proceedings of the ICRA 2013 Workshop on Autonomous Learning, Karslruhe, 2013 |
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| Proceedings of the ECAI-12 Workshop on Preference Learning: Problems and Applications in AI (PL-12), 2012 |
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| and , Preference Learning, in: Encyclopedia of the Sciences of Learning, pages 986, Springer-Verlag, 2012 |
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| and , Error-Correcting Output Codes as a Transformation from Multi-Class to Multi-Label Prediction, in: Proceedings of the 15th International Conference on Discovery Science (DS-12), pages 254--267, Springer, 2012 |
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| and , First Steps Towards Learning from Game Annotations, in: Proceedings of the {ECAI} Workshop on Preference Learning: Problems and Applications in AI, Montpellier, pages 53-58, 2012 |
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| and , Multidimensional Ordered Mappings for Empirical Machine Learning Research, KDML 2012, 2012 |
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| , , and , Multi-label LeGo -- Enhancing Multi-label Classifiers with Local Patterns, Knowledge Engineering Group, Technische Universität Darmstadt, number TUD-KE-2012-02, 2012 |
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| , , and , Preference-based Reinforcement Learning: A Formal Framework and a Policy Iteration Algorithm (2012), in: Machine Learning, 89:1-2(123--156) |
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| and , Probability Estimation and Aggregation for Rule Learning, in: Proceedings of the German Workshop on Lernen, Wissen, Adaptivität - LWA2010, Kassel, Germany, pages 143--150, 2010 |
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| and , Basic Instrument for Experimental Probes in Machine Learning, Knowledge Engineering Group, Technische Universität Darmstadt, number TUD–KE–2012–01, 2012 |
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| , , and , Multi-label LeGo -- Enhancing Multi-label Classifiers with Local Patterns, in: Advances in Intelligent Data Analysis XI -- Proceedings of the 11th International Symposium on Data Analysis (IDA-11), Berlin, pages 114--125, Springer, 2012 |
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| and , Unsupervised Generation of Data Mining Features from Linked Open Data, in: International Conference on Web Intelligence and Semantics (WIMS'12), 2012 |
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| and , Unsupervised Generation of Data Mining Features from Linked Open Data, Knowledge Engineering Group, Technische Universität Darmstadt, number TUD-KE-2011-2, 2011 |
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| and , Learning from Label Preferences, in: Proceedings of the 22nd International Conference on Algorithmic Learning Theory (ALT-11), pages 38, Springer, 2011 |
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| and , Rule Stacking: An Approach for Compressing an Ensemble of Rule Sets into a Single Classifier, in: Proceedings of the 14th International Conference on Discovery Science (DS-11), pages 323--334, Springer, 2011 |
[DOI] |
| and , Learning from Label Preferences, in: Proceedings of the 14th International Conference on Discovery Science (DS-11), pages 2--17, Springer, 2011 |
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| and , Margin Driven Separate and Conquer by Assymmetric Loss Functions, TU Darmstadt, Knowledge Engineering Group, number TUD–KE–2011–01, 2011 |
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| and , Heuristic Rule-Based Regression via Dynamic Reduction to Classification, in: Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI-11), Barcelona, Spain, pages 1330--1335, 2011 |
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| and , Separate-and-conquer Regression, in: Proceedings of the German Workshop on Lernen, Wissen, Adaptivität - LWA2010, Kassel, Germany, pages 81--89, 2010 |
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| , , and , Preference-Based Policy Iteration: Leveraging Preference Learning for Reinforcement Learning, in: Proceedings of the 22nd European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2011, Athens, Greece), Part I, pages 312--327, Springer, 2011 |
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| and , Efficient prediction algorithms for binary decomposition techniques (2012), in: Data Mining and Knowledge Discovery, 24:1(40-77) |
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| , Pruning, in: Encyclopedia of Machine Learning, pages 817, Springer-Verlag, 2010 |
| , Decision Lists and Decision Trees, in: Encyclopedia of Machine Learning, pages 261--262, Springer-Verlag, 2010 |
| , Decision List, in: Encyclopedia of Machine Learning, pages 261, Springer-Verlag, 2010 |
| , Web Mining, in: Data Mining and Knowledge Discovery Handbook, pages 913--930, Springer-Verlag, 2010 |
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| , and , Exploiting Code Redundancies in ECOC, in: Proceedings of the 13th International Conference on Discovery Science (DS-10), pages 266--280, Springer, 2010 |
[DOI] |
| and , On Exploiting Hierarchical Label Structure with Pairwise Classifiers (2010), in: SIGKDD Explorations, 12:2(21--25) |
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| and , Preference Learning and Ranking by Pairwise Comparison, in: Preference Learning, pages 65--82, Springer-Verlag, 2010 |
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| and , Preference Learning: An Introduction, in: Preference Learning, pages 1--17, Springer-Verlag, 2010 |
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| Preference Learning, Springer-Verlag, 2010 |
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| and , A Moderately Successful Attempt to Train Chess Evaluation Functions of Different Strengths, in: Proceedings of the ICML-10 Workshop on Machine Learning and Games, 2010 |
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| and , A Moderately Successful Attempt to Train Chess Evaluation Functions of Different Strengths, TU Darmstadt, number TUD-KE-2010-07, 2010 |
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| , and , Exploiting Code-Redundancies in ECOC for Reducing its Training Complexity using Incremental and SVM Learners, TU Darmstadt, number TUD-KE-2010-06, 2010 |
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| and , Rule Stacking: An approach for compressing an ensemble of rule sets into a single classifier, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2010-05, 2010 |
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| and , Probability Estimation and Aggregation for Rule Learning, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2010-03, 2010 |
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| and , A Review and Comparison of Strategies for Handling Missing Values in Separate-and-Conquer Rule Learning (2011), in: Journal of Intelligent Information Systems, 36:1(73--98) |
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| and , Learning to Recognize Missing E-mail Attachments (2010), in: Applied Artificial Intelligence, 24:5(443-462) |
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| and , The SeCo-framework for rule learning, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2010-02, 2010 |
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| and , Separate-and-conquer Regression, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2010-01, 2010 |
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| and , Guest Editorial: Global Modeling using Local Patterns (2010), in: Data Mining and Knowledge Discovery, 21:1(1--8) |
[DOI] |
| , Decision Tree, in: Encyclopedia of Machine Learning, pages 263--267, Springer-Verlag, 2010 |
| and , Margin Driven Separate and Conquer by Working Set Expansion, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2009-06, 2009 |
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| , Application of Clausal Discovery to Temporal Databases, in: Proceedings of the MLnet Familiarization Workshop on Data Mining with Inductive Logic Programming, pages 25--40, 1996 |
| and , Relational Knowledge Discovery in Databases, in: Proceedings of the MLnet Familiarization Workshop on Data Mining with Inductive Logic Programming, pages 111--124, 1996 |
| and , Direct Access of an ILP Algorithm to a Database Management System, in: Proceedings of the MLnet Familiarization Workshop on Data Mining with Inductive Logic Programming, pages 95--110, 1996 |
| , and , An application of ILP in a Musical Database: Learning to Compose the Two-Voice Counterpoint, in: Proceedings of the MLnet Familiarization Workshop on Data Mining with Inductive Logic Programming (ILP for KDD), 1996 |
| , and , Efficient Voting Prediction for Pairwise Multilabel Classification (2010), in: Neurocomputing, 73:7-9(1164 - 1176) |
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| and , Learning To Recognize Missing E-mail Attachments, Knowledge Engineering Group, TU Darmstadt, number TUD-KE-2009-05, 2009 |
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| and , Improving the Ranking Performance of Decision Trees, in: Proceedings of the 17th European Conference on Machine Learning (ECML-06), pages 461--472, Springer-Verlag, 2006 |
| and , Pattern Teams, in: Proceedings of the 10th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD-06), pages 577--584, Springer-Verlag, 2006 |
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| , and , Millions of Random Rules, in: Proceedings of the ECML/PKDD Workshop on Advances in Inductive Rule Learning, 2005 |
| and , Combining Pairwise Classifiers with Stacking, in: Advances in Intelligent Data Analysis: Proceedings of the 5th International Symposium (IDA-03), pages 219--229, Springer-Verlag, 2003 |
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| , Modeling Rule Precision, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2003-35, 2003 |
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| Preference Learning: Models, Methods, Applications -- Proceedings of the KI-2003 Workshop, Austrian Research Institute for Artificial Intelligence, 2003 |
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| and , Pairwise Preference Learning and Ranking, in: Preference Learning: Models, Methods, Applications -- Proceedings of the KI-2003 Workshop, 2003 |
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| and , Pairwise Preference Learning and Ranking, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2003-14, 2003 |
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| and , An Analysis of Rule Evaluation Metrics, in: Proceedings of the 20th International Conference on Machine Learning (ICML-03), pages 202--209, AAAI Press, 2003 |
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| and , An Analysis of Rule Learning Heuristics, Department of Computer Science, University of Bristol, number CSTR-03-002, 2003 |
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| , and , On the Cultural Evoluation of Age-at-marriage Norms, in: Agent-Based Computational Demography, pages 139--157, Physica-Verlag / Springer, 2003 |
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| , Round Robin Ensembles (2003), in: Intelligent Data Analysis, 7:5(385--404) |
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| , Round Robin Ensembles, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2002-37, 2002 |
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| , , and , On the Use of Fast Subsampling Estimates for Algorithm Recommendation, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2002-36, 2002 |
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| , Web Structure Mining --- Exploiting the Graph Structure of the World-Wide Web (2002), in: ÖGAI Journal, 21:2(17--26) |
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| , Web Structure Mining --- Exploiting the Graph Structure of the World-Wide Web, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2002-33, 2002 |
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| , A Pathology of Bottom-Up Hill-Climbing in Inductive Rule Learning, in: Proceedings of the 13th European Conference on Algorithmic Learning Theory (ALT-02), pages 263--277, Springer-Verlag, 2002 |
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| , A Pathology of Bottom-Up Hill-Climbing in Inductive Rule Learning, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2002-28, 2002 |
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| , Pairwise Classification as an Ensemble Technique, in: Proceedings of the 13th European Conference on Machine Learning (ECML-02), pages 97--110, Springer-Verlag, 2002 |
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| , Pairwise Classification as an Ensemble Technique, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2002-20, 2002 |
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| , Hyperlink Ensembles: A Case Study in Hypertext Classification (2002), in: Information Fusion, 3:4(299--312) |
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| , Hyperlink Ensembles: A Case Study in Hypertext Classification, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2001-30, 2001 |
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| , and , User Profiling for the Melvil Knowledge Retrieval System (2002), in: Applied Artificial Intelligence, 16:4(243--281) |
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| , and , User Profiling for the Melvil Knowledge Retrieval System, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2001-29, 2001 |
[URL] |
| , Inductive Rule Learning for Data and Web Mining, Habilitationsschrift, Technisch-Naturwissenschaftliche Fakult{\"a}t, Technische Universi{\"a}t Wien, 2001 |
| , Round Robin Classification (2002), in: Journal of Machine Learning Research, 2(721--747) |
[URL] |
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