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 journal and type
AI Communications
| , Efficient Pruning Methods for Relational Learning (Extended Thesis Abstract) (1995), in: AI Communications, 8:2(105--106) |
[URL] |
American Behavioral Scientist
| , and , Advances in Machine Learning for the Behavioral Sciences (2020), in: American Behavioral Scientist, 64:2(145--175) |
[DOI] [URL] |
Applied Artificial Intelligence
| and , Learning to Recognize Missing E-mail Attachments (2010), in: Applied Artificial Intelligence, 24:5(443-462) |
[DOI] |
| , and , User Profiling for the Melvil Knowledge Retrieval System (2002), in: Applied Artificial Intelligence, 16:4(243--281) |
[URL] |
| and , Guest Editorial: First-Order Knowledge Discovery in Databases (1998), in: Applied Artificial Intelligence, 12:5(345--361) |
[URL] |
| and , Special Issue on First-Order Knowledge Discovery in Databases (1998), in: Applied Artificial Intelligence, 12:5 |
[URL] |
| , and , Knowledge Discovery in International Conflict Databases (1997), in: Applied Artificial Intelligence, 11:2(91--118) |
[URL] |
Archives of Data Science, Series A
| , , 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 |
Artificial Intelligence
| , , and , Label Ranking by Learning Pairwise Preferences (2008), in: Artificial Intelligence, 172:16–17(1897--1916) |
[DOI] |
Artificial Intelligence Review
| , Separate-and-Conquer Rule Learning (1999), in: Artificial Intelligence Review, 13:1(3--54) |
[URL] |
arXiv preprint arXiv:1412.6881
| and , On Learning Vector Representations in Hierarchical Label Spaces (2014), in: arXiv preprint arXiv:1412.6881 |
[URL] |
arXiv preprint arXiv:1803.01316
| , and , On Cognitive Preferences and the Plausibility of Rule-based Models (2018), in: arXiv preprint arXiv:1803.01316 |
[URL] |
Computers
| , 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] |
CoRR
| , , and , Correlation-based Discovery of Disease Patterns for Syndromic Surveillance (2021), in: CoRR, abs/2110.09208 |
[URL] |
| , and , Revisiting Non-Specific Syndromic Surveillance (2021), in: CoRR, abs/2101.12246 |
[URL] |
Cybernetics and Systems
| , , , , and , Searching for Patterns in Political Event Sequences: Experiments with the KEDS Database (2000), in: Cybernetics and Systems, 31:6(649--668) |
[URL] |
Dagstuhl Reports
| , , , and , Preference Learning (Dagstuhl Seminar 14101) (2014), in: Dagstuhl Reports, 4:3(1--27) |
[DOI] [URL] |
Data Mining and Knowledge Discovery
| and , Efficient prediction algorithms for binary decomposition techniques (2012), in: Data Mining and Knowledge Discovery, 24:1(40-77) |
[DOI] 
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| and , Guest Editorial: Global Modeling using Local Patterns (2010), in: Data Mining and Knowledge Discovery, 21:1(1--8) |
[DOI] |
European Journal of Population
| , and , Timing, Sequencing, and Quantum of Life Course Events: A Machine Learning Approach (2006), in: European Journal of Population, 22:1(37--65) |
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Expert Systems with Applications
| , , and , Refinement and Selection Heuristics in Subgroup Discovery and Classification Rule Learning (2017), in: Expert Systems with Applications, 81(147--162) |
[DOI] |
Frontiers in Big Data
| , , and , Correlation-based Discovery of Disease Patterns for Syndromic Surveillance (2021), in: Frontiers in Big Data |
IEEE Transactions on Computational Intelligence and AI in Games
| and , On Learning from Game Annotations (2015), in: IEEE Transactions on Computational Intelligence and AI in Games, 7:3(304-316) |
[DOI] |
IEEE Transactions on Games
| , , , and , Informed Hybrid Game Tree Search (2018), in: IEEE Transactions on Games, 10:1(78--90) |
[DOI] [URL] |
ILP Newsletter
| and , Summary of the Workshop on ILP for KDD (1997), in: ILP Newsletter, 4:1 |
[URL] |
Information Fusion
| , Hyperlink Ensembles: A Case Study in Hypertext Classification (2002), in: Information Fusion, 3:4(299--312) |
[URL] |
Information Sciences
| and , Special Issue on Discovery Science (2016), in: Information Sciences, 329(849--850) |
[DOI] |
Intelligent Data Analysis
| , Round Robin Ensembles (2003), in: Intelligent Data Analysis, 7:5(385--404) |
[URL] |
International Computer Chess Association Journal
| and , Workshop Report: Machine Learning in Game Playing (1999), in: International Computer Chess Association Journal, 22:3(178,179,165) |
[URL] |
| and , A Hypothesis on the Divergence of AI Research (1998), in: International Computer Chess Association Journal, 21:1(3--13) |
[URL] |
| , Machine Learning in Computer Chess: The Next Generation (1996), in: International Computer Chess Association Journal, 19:3(147--161) |
[URL] |
International Computer Games Association Journal
| and , Learning the Piece Values for Three Chess Variants (2008), in: International Computer Games Association Journal, 31:4(209--233) |
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Journal of Artificial Intelligence Research
| , Integrative Windowing (1998), in: Journal of Artificial Intelligence Research, 8(129--164) |
[URL] |
Journal of Classification
| , , and , Comparing Boosting and Bagging for Decision Trees of Rankings (2021), in: Journal of Classification |
[DOI] [URL] |
Journal of Computer and System Sciences
| and , On Predictive Accuracy and Risk Minimization in Pairwise Label Ranking (2010), in: Journal of Computer and System Sciences, 76:1(49--62) |
[DOI] |
Journal of Intelligent Information Systems
| 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) |
[DOI] |
Journal of Machine Learning Research
| , , and , A Survey of Preference-Based Reinforcement Learning Methods (2017), in: Journal of Machine Learning Research, 18:136(1--46) |
[URL] |
| , Round Robin Classification (2002), in: Journal of Machine Learning Research, 2(721--747) |
[URL] |
Künstliche Intelligenz
| and , Preference Learning (2005), in: Künstliche Intelligenz, 19:1(60--61) |
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Machine Learning
| and , Efficient Implementation of Class-Based Decomposition Schemes for Naive Bayes (2014), in: Machine Learning, 96:3(295--309) |
[DOI] |
| and , Editorial: Preference Learning and Ranking (2013), in: Machine Learning, 93:2-3(185--189) |
[URL] |
| Special Issue on Preference Learning and Ranking (2013), in: Machine Learning, 93:2-3 |
[URL] |
| , , and , Preference-based Reinforcement Learning: A Formal Framework and a Policy Iteration Algorithm (2012), in: Machine Learning, 89:1-2(123--156) |
[DOI] |
| and , On the Quest for Optimal Rule Learning Heuristics (2010), in: Machine Learning, 78:3(343--379) |
[DOI]
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| , , and , Multilabel Classification via Calibrated Label Ranking (2008), in: Machine Learning, 73:2(133--153) |
[DOI]
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| , , and , Guest Editorial: Machine Learning and Games (2006), in: Machine Learning, 63:3(211--215) |
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| , , and , Special Issue on Machine Learning and Games (2006), in: Machine Learning, 63:3 |
[URL] |
| and , ROC 'n' Rule Learning -- Towards a Better Understanding of Covering Algorithms (2005), in: Machine Learning, 58:1(39--77) |
[DOI] [URL] |
| , Pruning Algorithms for Rule Learning (1997), in: Machine Learning, 27:2(139--171) |
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Machine Learning Journal
| , , , and , A Flexible Class of Dependence-sensitive Multi-label Loss Functions (2021), in: Machine Learning Journal |
[URL] |
| , , and , Tree-Based Dynamic Classifier Chains (2021), in: Machine Learning Journal |
[URL] |
MLnet News
| and , Summary of the Workshop on ILP for KDD (1996), in: MLnet News, 4:2(16) |
[URL] |
Neurocomputing
| , and , Efficient Voting Prediction for Pairwise Multilabel Classification (2010), in: Neurocomputing, 73:7-9(1164 - 1176) |
[DOI]
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ÖGAI Journal
| , Recent Advances in Machine Learning and Game Playing (2007), in: ÖGAI Journal, 26:2 |
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| , Web Structure Mining --- Exploiting the Graph Structure of the World-Wide Web (2002), in: ÖGAI Journal, 21:2(17--26) |
[URL] |
ÖGAI--Journal
| and , Bericht über ILP-98, ICML-98 und AAAI-98 (1998), in: ÖGAI--Journal, 17:3(2--9) |
| , Bericht über IJCAI-97 und AAAI-97 (1997), in: ÖGAI--Journal, 16:3(30--33) |
| , A Brief Introduction to Knowledge Discovery in Databases (1995), in: ÖGAI--Journal, 14:4(14--17) |
[URL] |
| , Bericht über The 11th International Conference on Machine Learning (ML-94) (1994), in: ÖGAI--Journal, 13:2(3--4) |
| , Inductive Logic Programming (A Short Introduction and a Thesis Abstract) (1994), in: ÖGAI--Journal, 13:3--4(3--8) |
[URL] |
| , Bericht über The 13th International Conference on Artificial Intelligence (IJCAI-93) (1993), in: ÖGAI--Journal, 12:1--2(10--12) |
SIGKDD Explorations
| and , On Exploiting Hierarchical Label Structure with Pairwise Classifiers (2010), in: SIGKDD Explorations, 12:2(21--25) |
[URL] |
Urban Science
| , , and , Determining Factors for Slum Growth with Predictive Data Mining Methods (2018), in: Urban Science, 2:3(81:1--81:19) |
[DOI] [URL] |
2012
| , and , Foundations of Rule Learning, Springer-Verlag, 2012 |
[DOI] [URL] |
2010
| Preference Learning, Springer-Verlag, 2010 |
[DOI] [URL] |
2001
| Machines that Learn to Play Games, Nova Science Publishers, Advances in Computation: Theory and Practice, volume 8, 2001 |
[URL] |
2018
| , , 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 |
[DOI] [URL] |
2013
| , Rule-Based Methods, in: Encyclopedia of Systems Biology, Springer-Verlag, 2013 |
2012
| and , Preference Learning, in: Encyclopedia of the Sciences of Learning, pages 986, Springer-Verlag, 2012 |
[DOI] |
2010
| , Decision List, in: Encyclopedia of Machine Learning, pages 261, Springer-Verlag, 2010 |
| , Decision Lists and Decision Trees, in: Encyclopedia of Machine Learning, pages 261--262, Springer-Verlag, 2010 |
| , Decision Tree, in: Encyclopedia of Machine Learning, pages 263--267, Springer-Verlag, 2010 |
| and , Efficient Multilabel Classification Algorithms for Large-Scale Problems in the Legal Domain, in: Semantic Processing of Legal Texts -- Where the Language of Law Meets the Law of Language, pages 192-215, Springer-Verlag, 2010 |
[DOI]
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| , and , Explicit Feature Construction and Manipulation for Covering Rule Learning Algorithms, in: Advances in Machine Learning I --- Dedicated to the Memory of Professor Ryszard S. Michalski, pages 121--146, Springer-Verlag, 2010 |
[DOI] |
| , Machine Learning and Game Playing, in: Encyclopedia of Machine Learning, pages 633--637, Springer-Verlag, 2010 |
| and , Preference Learning, in: Encyclopedia of Machine Learning, pages 789--795, Springer-Verlag, 2010 |
| and , Preference Learning and Ranking by Pairwise Comparison, in: Preference Learning, pages 65--82, Springer-Verlag, 2010 |
[DOI]
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| and , Preference Learning: An Introduction, in: Preference Learning, pages 1--17, Springer-Verlag, 2010 |
[DOI]
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| , Pruning, in: Encyclopedia of Machine Learning, pages 817, Springer-Verlag, 2010 |
| , Rule Learning, in: Encyclopedia of Machine Learning, pages 875--879, Springer-Verlag, 2010 |
| , Web Mining, in: Data Mining and Knowledge Discovery Handbook, pages 913--930, Springer-Verlag, 2010 |
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2008
| and , Learning Preference Models from Data: On the Problem of Label Ranking and Its Variants, in: Preferences and Similarities, pages 283--304, Springer-Verlag, 2008 |
[DOI]
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2006
| and , Link-local Features for Hypertext Classification, in: Semantics, Web and Mining, pages 51--64, Springer-Verlag, 2006 |
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| , and , Modeling International Negotiation: Statistical and Machine Learning Approaches, in: Programming for Peace: Computer-Aided Methods for International Conflict Resolution and Prevention, pages 227--250, Kluwer Academic Publishers, 2006 |
[URL] |
2005
| , Web Mining, in: Data Mining and Knowledge Discovery Handbook, pages 899--920, Springer-Verlag, 2005 |
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2003
| , and , On the Cultural Evoluation of Age-at-marriage Norms, in: Agent-Based Computational Demography, pages 139--157, Physica-Verlag / Springer, 2003 |
[URL] |
2001
| , Machine Learning in Games: A Survey, in: Machines that Learn to Play Games, pages 11--59, Nova Science Publishers, 2001 |
[URL] |
2021
| , , and , Gradient-Based Label Binning in Multi-Label Classification, in: Machine Learning and Knowledge Discovery in Databases (ECML-PKDD), Springer, 2021 |
[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 |
[DOI] [URL] |
| , , and , Sum-Product Networks for Early Outbreak Detection of Emerging Diseases, in: Artificial Intelligence in Medicine, pages 61--71, Springer International Publishing, 2021 |
2020
| , and , Conformal Rule-Based Multi-label Classification, in: KI 2020: Advances in Artificial Intelligence, Springer, Cham, 2020 |
[DOI] [URL] |
| , 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 |
[DOI] |
| , , , and , Learning Gradient Boosted Multi-label Classification Rules, in: Machine Learning and Knowledge Discovery in Databases (ECML-PKDD), pages 124--140, Springer, 2020 |
[DOI] [URL] |
| , , and , Learning Structured Declarative Rule Sets — A Challenge for Deep Discrete Learning, in: 2nd Workshop on Deep Continuous-Discrete Machine Learning (DeCoDeML), 2020 |
[URL] |
| , , , and , On Aggregation in Ensembles of Multilabel Classifiers, in: Discovery Science, pages 533--547, Springer International Publishing, 2020 |
[DOI] [URL] |
| , , , and , Rule-Based Multi-label Classification: Challenges and Opportunities, in: Rules and Reasoning, pages 3--19, Springer International Publishing, 2020 |
[DOI] [URL] |
2019
| , and , Beta Distribution Drift Detection for Adaptive Classifiers, in: Proceedings of the 2019 European Symposium on Artificial Neural Networks -- ESANN'19, 2019 |
| and , Driver Information Embedding with Siamese LSTM networks, in: 2019 IEEE Intelligent Vehicles Symposium (IV), Paris, France, IEEE, 2019 |
[DOI] [URL] |
| , 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 |
[URL] |
| , 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 |
[DOI] [URL] |
| , , , , 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 |
[URL] |
| , 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 , On the Trade-off Between Consistency and Coverage in Multi-label Rule Learning Heuristics, in: Discovery Science, pages 96--111, Springer International Publishing, 2019 |
[DOI] [URL] |
| , and , Patching Deep Neural Networks for Nonstationary Environments, in: Proceedings of the 2019 International Joint Conference on Neural Networks -- IJCNN'19, 2019 |
2018
| and , Batchwise Patching of Classifiers, in: Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), pages 3374--3381, 2018 |
[URL] |
| , 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 |
[DOI] [URL] |
| 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 |
[URL] |
| 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 |
[URL] |
| , , , , , 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 |
[DOI] [URL] |
| , 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 |
[DOI] |
| , and , Preference-Based Monte Carlo Tree Search, in: Proceedings of the 41st German Conference on Artficial Intelligence (KI-18), pages 327--340, Springer, 2018 |
[DOI] [URL] |
| 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 |
[DOI] |
| , 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 , 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 |
[DOI] [URL] |
| , 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 |
[DOI] [URL] |
2017
| , 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 |
[DOI] [URL] |
| , , 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 |
[URL] |
| , , 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 |
[DOI] |
| , 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 |
[DOI]
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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 |
[DOI] [URL] |
2016
| , 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 |
[URL] |
| , 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 |
[URL] |
| , 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 |
[URL] |
| , 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 |
[DOI] [URL] |
| , 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 |
[URL] |
| , 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 |
[DOI] [URL] |
| , , 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 |
[URL] |
| , 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 |
[URL] |
2015
| 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 |
[URL] |
| , , 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 |
[URL] |
| , , 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 |
[URL] |
| , , 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 |
[DOI]
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2014
| , and , Graded Multilabel Classification by Pairwise Comparisons, in: 2014 IEEE International Conference on Data Mining (ICDM 2014), pages 731--736, Curran Associates, IEEE, 2014 |
[DOI]
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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 , 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 |
[DOI]
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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 |
[URL] |
| , 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 |
[DOI] [URL] |
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 |
[DOI] |
| 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 |
[URL] |
| and , Learning from Trajectory-Based Action Preferences, in: Proceedings of the ICRA 2013 Workshop on Autonomous Learning, Karslruhe, 2013 |
[URL] |
| 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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2012
| 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 |
[DOI] |
| 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 , 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 |
[DOI]
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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 |
[DOI] |
2011
| 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 |
[URL] |
| and , Learning from Label Preferences, in: Proceedings of the 14th International Conference on Discovery Science (DS-11), pages 2--17, Springer, 2011 |
[DOI] |
| and , Learning from Label Preferences, in: Proceedings of the 22nd International Conference on Algorithmic Learning Theory (ALT-11), pages 38, Springer, 2011 |
[DOI] |
| , , 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 , 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] |
2010
| 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 , Exploiting Code Redundancies in ECOC, in: Proceedings of the 13th International Conference on Discovery Science (DS-10), pages 266--280, Springer, 2010 |
[DOI] |
| 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 |
[URL] |
| and , Separate-and-conquer Regression, in: Proceedings of the German Workshop on Lernen, Wissen, Adaptivität - LWA2010, Kassel, Germany, pages 81--89, 2010 |
[URL] |
2009
| and , A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning, in: Proceedings of the SIAM International Conference on Data Mining (SDM-09), pages 329--340, 2009 |
[URL] |
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| and , An Empirical Comparison of Probability Estimation Techniques for Probabilistic Rules, in: Proceedings of the 12th International Conference on Discovery Science (DS-09), Porto, Portugal, pages 317--331, Springer-Verlag, 2009 |
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| and , On Table Extraction from Text Sources with Markups, in: Proceedings of the LWA 2009: Lernen -- Wissen -- Adaption, Workshop Information Retrieval (WIR-09), pages 1--8, 2009 |
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| , , , and , On the Combination of Two Decompositive Multi-Label Classification Methods, in: Proceedings of the ECML PKDD 2009 Workshop on Preference Learning (PL-09, Bled, Slovenia), pages 114--129, 2009 |
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2008
| and , A Comparison of Techniques for Selecting and Combining Class Association Rules, in: From Local Patterns to Global Models: Proceedings of the ECML/PKDD-08 Workshop (LeGo-08), pages 154--168, 2008 |
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| and , A Comparison of Techniques for Selecting and Combining Class Association Rules, in: Proceedings of the LWA 2008: Lernen -- Wissen -- Adaption, pages "", 2008 |
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| and , An Evaluation of Efficient Multilabel Classification Algorithms for Large-Scale Problems in the Legal Domain, in: Proceedings of the LREC 2008 Workshop on Semantic Processing of Legal Texts, pages 23-32, 2008 |
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| and , Efficient Pairwise Multilabel Classification for Large-Scale Problems in the Legal Domain, in: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Disocvery in Databases (ECML-PKDD-2008), Part II, pages 50--65, Springer, 2008 |
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| , , and , From Local Patterns to Global Models: The LeGo Approach to Data Mining, in: From Local Patterns to Global Models: Proceedings of the ECML/PKDD-08 Workshop (LeGo-08), pages 1--16, 2008 |
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| , and , Handling Unknown and Imprecise Attribute Values in Propositional Rule Learning: A Feature-Based Approach, in: Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence (PRICAI-08), pages 636--645, Springer-Verlag, 2008 |
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2007
| and , An Evaluation of Efficient Multilabel Classification Algorithms for Large-Scale Problems in the Legal Domain, in: Proceedings of the LWA 2007: Lernen - Wissen - Adaption, pages 126--132, 2007 |
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| and , Efficient Pairwise Classification, in: Proceedings of the 18th European Conference on Machine Learning (ECML 2007, Warsaw, Poland), pages 658--665, Springer-Verlag, 2007 |
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| and , Meta-Learning Rule Learning Heuristics, in: Proceedings of ECML-PKDD-07 Workshop on Planning to Learn (PlanLearn-07), pages 9-21, 2007 |
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| and , Meta-Learning Rule Learning Heuristics, in: Proceedings of the German Workshop on Lernen, Wissen, Adaptivität - LWA2007, pages 167--174, 2007 |
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| and , On Minimizing the Position Error in Label Ranking, in: Proceedings of 18th European Conference on Machine Learning (ECML-07), pages 583--590, Springer-Verlag, 2007 |
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| , and , On Pairwise Naive Bayes Classifiers, in: Proceedings of 18th European Conference on Machine Learning (ECML-07), pages 371--381, Springer-Verlag, 2007 |
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2006
| , and , A Unified Model for Multilabel Classification and Ranking, in: Proceedings of the 17th European Conference on Artificial Intelligence (ECAI-06), pages 489--493, 2006 |
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| and , Case-Based Label Ranking, in: Proceedings of the 17th European Conference on Machine Learning (ECML-06), pages 566--573, Springer-Verlag, 2006 |
| 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 , On Trading Off Consistency and Coverage in Inductive Rule Learning, in: Proceedings of the German Workshop on Lernen, Wissen, Adaptivität - LWA2006, pages 306--313, Gesellschaft für Informatik e. V. (GI), 2006 |
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2005
| , From Local to Global Patterns: Evaluation Issues in Rule Learning Algorithms, in: Local Pattern Detection, pages 20--38, Springer-Verlag, 2005 |
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| and , Learning Label Preferences: Ranking Error versus Position Error, in: Advances in Intelligent Data Analysis: Proceedings of the 6th International Symposium (IDA-05), pages 180--191, Springer-Verlag, 2005 |
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| and , Link-local Features for Hypertext Classification, in: Proceedings of the European Web Mining Forum (EWMF-05): Workshop at ECML/PKDD-05, pages 40--51, 2005 |
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| , and , Millions of Random Rules, in: Proceedings of the ECML/PKDD Workshop on Advances in Inductive Rule Learning, 2005 |
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2004
| and , An Analysis of Stopping and Filtering Criteria for Rule Learning, in: Proceedings of the 15th European Conference on Machine Learning (ECML-04), pages 123--133, Springer-Verlag, 2004 |
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| and , Comparison of Ranking Procedures in Pairwise Preference Learning, in: Proceedings of the 10th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU-04), 2004 |
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| , Modeling Rule Precision, in: Proceedings of the ECML/PKDD-04 Workshop on Advances in Inductive Rule Learning, pages 30--45, 2004 |
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2003
| 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 , 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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| and , Pairwise Preference Learning and Ranking, in: Proceedings of the 14th European Conference on Machine Learning (ECML-03), pages 145--156, Springer-Verlag, 2003 |
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2002
| , 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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| , 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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2001
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2000
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1999
| , Exploiting Structural Information for Text Classification on the WWW, in: Advances in Intelligent Data Analysis: Proceedings of the 3rd International Symposium (IDA-99), pages 487--497, Springer-Verlag, 1999 |
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1998
| , and , A Case Study in Using Linguistic Phrases for Text Categorization on the WWW, in: Learning for Text Categorization: Proceedings of the 1998 AAAI/ICML Workshop, pages 5--12, AAAI Press, 1998 |
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1997
| , Dimensionality Reduction in ILP: A Call to Arms, in: Proceedings of the IJCAI-97 Workshop on Frontiers of Inductive Logic Programming, pages 81--86, 1997 |
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| , More Efficient Windowing, in: Proceedings of the 14th National Conference on Artificial Intelligence (AAAI-97), pages 509-514, AAAI Press, 1997 |
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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 |
| , 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 |
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1995
| , A Tight Integration of Pruning and Learning (Extended Abstract), in: Proceedings of the 8th European Conference on Machine Learning (ECML-95), pages 291--294, Springer-Verlag, 1995 |
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1994
| , A Comparison of Pruning Methods for Relational Concept Learning, in: Knowledge Discovery in Databases: Papers from the 1994 AAAI Workshop (KDD-94), pages 371--382, AAAI Press, 1994 |
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| and , Incremental Reduced Error Pruning, in: Proceedings of the 11th International Conference on Machine Learning (ML-94), pages 70--77, Morgan Kaufmann, 1994 |
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| , Pruning Methods for Rule Learning Algorithms, in: Proceedings of the 4th International Workshop on Inductive Logic Programming (ILP-94), pages 321--336, 1994 |
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| , Top-Down Pruning in Relational Learning, in: Proceedings of the 11th European Conference on Artificial Intelligence (ECAI-94), pages 453--457, John Wiley \& Sons, 1994 |
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| , {\sc Fossil}: {A} Robust Relational Learner, in: Proceedings of the 7th European Conference on Machine Learning (ECML-94), pages 122--137, Springer-Verlag, 1994 |
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1993
| , Avoiding Noise Fitting in a {\sc Foil}-like Learning Algorithm, in: Proceedings of the IJCAI-93 Workshop on Inductive Logic Programming, pages 14--23, 1993 |
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1991
| , Induktives Lernen durch Generieren von Decision Trees, Vienna University of Technology, 1991 |
2012
| and , Multidimensional Ordered Mappings for Empirical Machine Learning Research, KDML 2012, 2012 |
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2001
| , Inductive Rule Learning for Data and Web Mining, Habilitationsschrift, Technisch-Naturwissenschaftliche Fakult{\"a}t, Technische Universi{\"a}t Wien, 2001 |
1997
| and , Learning Playing Strategies from Chess Endgame Databases: An ILP Approach, Unpublished, Leuven, 1997 |
1995--2000
| , Bibliography on Machine Learning in Strategic Game Playing, \url{/~juffi/lig/}, 1995--2000 |
1994
| , and , The Potential Contribution of AI to the Avoidance of Crises and Wars: Bibliography, Unpublished Manuscript, 1994 |
| , and , The Potential Contribution of AI to the Avoidance of Crises and Wars: International Conflict Databases and Machine Learning, Unpublished Manuscript, 1994 |
1993
| , A Numerical Analysis of the KRK Domain, Working Note, 1993 |
| , Application of Machine Learning Methods to the KOSIMO Database, Paper presented at the International Workshop on the Potential Contribution of Artificial Intelligence to the Avoidance of Crises and Wars, Vienna, 1993 |
1990
| , Explanation-Based Learning in der Domäne Schach, Unpublished Manuscript, 1990 |
1994
| , Efficient Pruning Methods for Relational Learning, Vienna University of Technology, 1994 |
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2017
| KI 2017: Advances in Artificial Intelligence, Springer-Verlag, 2017 |
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2013
| Proceedings of the 16th International Conference on Discovery Science (DS-13), Springer-Verlag, 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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2012
| Proceedings of the ECAI-12 Workshop on Preference Learning: Problems and Applications in AI (PL-12), 2012 |
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2010
2009
2008
2006
| Knowledge Discovery in Databases: PKDD 2006, Springer-Verlag, 2006 |
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| Machine Learning: ECML 2006, Springer-Verlag, 2006 |
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2005
| LWA 2005, Lernen Wissensentdeckung Adaptivität, German Research Center for Artificial Intelligence (DFKI), 2005 |
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2004
2003
| Preference Learning: Models, Methods, Applications -- Proceedings of the KI-2003 Workshop, Austrian Research Institute for Artificial Intelligence, 2003 |
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1999
| Proceedings of the ICML-99 Workshop on Machine Learning in Game Playing, J. Stefan Institute (IJS), 1999 |
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1996
| Proceedings of the MLnet Familiarization Workshop on Data Mining with Inductive Logic Programming (ILP for KDD), 1996 |
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2019
| , 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 , 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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2017
| , , 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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2016
| , , , and , Informed Hybrid Game Tree Search, Knowledge Engineering Group, Technische Universität Darmstadt, number TUD–KE–2016–01, 2016 |
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2015
| , 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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2014
| , and , Graded Multilabel Classification by Pairwise Comparisons, Knowledge Engineering Group, Technische Universität Darmstadt, Technical Report, 2014 |
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2012
| and , Basic Instrument for Experimental Probes in Machine Learning, Knowledge Engineering Group, Technische Universität Darmstadt, number TUD–KE–2012–01, 2012 |
|
| , , 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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2011
| and , Margin Driven Separate and Conquer by Assymmetric Loss Functions, TU Darmstadt, Knowledge Engineering Group, number TUD–KE–2011–01, 2011 |
|
| 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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2010
| and , A Moderately Successful Attempt to Train Chess Evaluation Functions of Different Strengths, TU Darmstadt, number TUD-KE-2010-07, 2010 |
|
| , and , Exploiting Code-Redundancies in ECOC for Reducing its Training Complexity using Incremental and SVM Learners, TU Darmstadt, number TUD-KE-2010-06, 2010 |
|
| and , Probability Estimation and Aggregation for Rule Learning, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2010-03, 2010 |
|
| 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 |
|
| and , Separate-and-conquer Regression, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2010-01, 2010 |
|
| and , The SeCo-framework for rule learning, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2010-02, 2010 |
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2009
| and , A Comparison of Strategies for Handling Missing Values in Rule Learning, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2009-03, 2009 |
|
| , , and , An Exploitative Monte-Carlo Poker Agent, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2009-02, 2009 |
|
| and , Efficient Decoding of Ternary Error-Correcting Output Codes for Multiclass Classification, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2009-01, 2009 |
|
| and , Learning To Recognize Missing E-mail Attachments, Knowledge Engineering Group, TU Darmstadt, number TUD-KE-2009-05, 2009 |
|
| 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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2008
| and , A Re-Evaluation of the Over-Searching Phenomenon in Inductive Rule Learning, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2008-02, 2008 |
|
| , and , Advances in Efficient Pairwise Multilabel Classification, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2008-06, 2008 |
|
| and , An Empirical Comparison of Techniques for Selecting and Combining Local Patterns into a Global Model, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2008-03, 2008 |
|
| and , An Empirical Quest for Optimal Rule Learning Heuristics, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2008-01, 2008 |
|
| and , Learning of Piece Values for Chess Variants, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2008-07, 2008 |
|
| and , Multi-Label Classification with Label Constraints, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2008-04, 2008 |
|
| and , On Table Extraction from Text Sources with Markups, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2008-05, 2008 |
|
2007
| and , Efficient Pairwise Classification and Ranking, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2007-03, 2007 |
|
| , , and , From Local Patterns to Global Models: The LeGo Approach to Data Mining, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2007-06, 2007 |
|
| , and , Label Ranking by Learning Pairwise Preferences, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2007-01, 2007 |
|
| and , Meta-Learning Rule Learning Heuristics, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2007-02, 2007 |
|
| and , On Minimizing the Position Error in Label Ranking, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2007-04, 2007 |
|
| and , Pairwise Learning of Multilabel Classifications with Perceptrons, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2007-05, 2007 |
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2003
| and , An Analysis of Rule Learning Heuristics, Department of Computer Science, University of Bristol, number CSTR-03-002, 2003 |
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| , Modeling Rule Precision, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2003-35, 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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2002
| , 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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| , , 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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| , Pairwise Classification as an Ensemble Technique, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2002-20, 2002 |
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| , Round Robin Ensembles, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2002-37, 2002 |
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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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2001
| and , An Evaluation of Landmarking Variants, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2001-13, 2001 |
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| , , and , Detecting Temporal Change in Event Sequences: An Application to Demographic Data, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2001-09, 2001 |
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| and , Grading Classifiers, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2001-01, 2001 |
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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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| , Round Robin Classification, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2001-18, 2001 |
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| , Round Robin Rule Learning, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2001-02, 2001 |
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2000
| , Machine Learning in Games: A Survey, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2000-31, 2000 |
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| , and , Timing, Sequencing, and Quantum of Life Course Events: A Machine Learning Approach, Max Planck Institute for Demographic Research, number WP 2000-010, MPIDR Working Paper, 2000 |
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1998
| , A Study Using $n$-gram Features for Text Categorization, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-98-30, 1998 |
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| , Using Links for Classifying Web-Pages, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-98-29, 1998 |
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1997
| , Dimensionality Reduction in ILP: A Call to Arms, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-97-26, 1997 |
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| , Knowledge Discovery in Chess Databases: A Research Proposal, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-97-33, 1997 |
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| , More Efficient Windowing, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-97-01, 1997 |
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| , Noise-Tolerant Windowing, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-97-07, 1997 |
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| and , On Effort in AI Research: A Description Along Two Dimensions, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-97-25, 1997 |
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1996
| , Digging for Peace: Using Machine Learning Methods for Assessing International Conflict Databases, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-96-10, 1996 |
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| , and , Knowledge Discovery in International Conflict Databases, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-96-24, 1996 |
| , Machine Learning in Computer Chess: The Next Generation, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-96-11, 1996 |
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| , Pruning Algorithms for Rule Learning, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-96-07, 1996 |
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| , Separate-and-Conquer Rule Learning, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-96-25, 1996 |
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1995
| , A Tight Integration of Pruning and Learning, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-95-03, 1995 |
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1994
| , A Comparison of Pruning Methods for Relational Concept Learning, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-94-16, 1994 |
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| and , Incremental Reduced Error Pruning, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-94-09, 1994 |
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| , , and , Machine Learning Methods for International Conflict Databases: A Case Study in Predicting Mediation Outcome, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-94-33, 1994 |
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| , Pruning Methods for Rule Learning Algorithms, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-94-26, 1994 |
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| , and , The Potential Contribution of AI to the Avoidance of Crises and Wars: Using CBR Methods with the KOSIMO Database of Conflicts, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-94-32, 1994 |
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| , Top-Down Pruning in Relational Learning, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-94-03, 1994 |
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1993
| , Avoiding Noise Fitting in a {\sc Foil}-like Learning Algorithm, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-93-16, 1993 |
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| , The Role of Qualitative Knowledge in Machine Learning, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-93-09, 1993 |
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| , {\sc Fossil}: {A} robust relational learner, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-93-28, 1993 |
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