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Luc De Raedt
2010 – today
- 2013
[j45]Tias Guns, Siegfried Nijssen, Luc De Raedt: k-Pattern Set Mining under Constraints. IEEE Trans. Knowl. Data Eng. 25(2): 402-418 (2013)- [c141]Martin Theobald, Luc De Raedt, Maximilian Dylla, Angelika Kimmig, Iris Miliaraki: 10 Years of Probabilistic Querying - What Next? ADBIS 2013: 1-13
- [c140]Bogdan Moldovan, Ingo Thon, Jesse Davis, Luc De Raedt: MCMC Estimation of Conditional Probabilities in Probabilistic Programming Languages. ECSQARU 2013: 436-448
- [c139]
- [c138]Tias Guns, Anton Dries, Guido Tack, Siegfried Nijssen, Luc De Raedt: MiningZinc: A Modeling Language for Constraint-Based Mining. IJCAI 2013
- [c137]Laura Antanas, McElory Hoffmann, Paolo Frasconi, Tinne Tuytelaars, Luc De Raedt: A relational kernel-based approach to scene classification. WACV 2013: 133-139
- [i11]Daan Fierens, Guy Van den Broeck, Joris Renkens, Dimitar Sht. Shterionov, Bernd Gutmann, Ingo Thon, Gerda Janssens, Luc De Raedt: Inference and learning in probabilistic logic programs using weighted Boolean formulas. CoRR abs/1304.6810 (2013)
- 2012
- [j44]Stephen Muggleton, Luc De Raedt, David Poole, Ivan Bratko, Peter A. Flach, Katsumi Inoue, Ashwin Srinivasan: ILP turns 20 - Biography and future challenges. Machine Learning 86(1): 3-23 (2012)
- [c136]
- [c135]
- [c134]Mathias Verbeke, Vincent Van Asch, Roser Morante, Paolo Frasconi, Walter Daelemans, Luc De Raedt: A Statistical Relational Learning Approach to Identifying Evidence Based Medicine Categories. EMNLP-CoNLL 2012: 579-589
- [c133]Thanh Le Van, Ana Carolina Fierroy, Tias Guns, Matthijs van Leeuwen, Siegfried Nijssen, Luc De Raedt, Kathleen Marchal: Mining Local Staircase Patterns in Noisy Data. ICDM Workshops 2012: 139-146
- [c132]
- [c131]Laura Antanas, Martijn van Otterlo, José Oramas M., Tinne Tuytelaars, Luc De Raedt: A Relational Distance-based Framework for Hierarchical Image Understanding. ICPRAM (2) 2012: 206-218
- [c130]Bogdan Moldovan, Plinio Moreno, Martijn van Otterlo, José Santos-Victor, Luc De Raedt: Learning relational affordance models for robots in multi-object manipulation tasks. ICRA 2012: 4373-4378
- [c129]
- [c128]Laura Antanas, Paolo Frasconi, Fabrizio Costa, Tinne Tuytelaars, Luc De Raedt: A Relational Kernel-Based Framework for Hierarchical Image Understanding. SSPR/SPR 2012: 171-180
- [p4]Angelika Kimmig, Esther Galbrun, Hannu Toivonen, Luc De Raedt: Patterns and Logic for Reasoning with Networks. Bisociative Knowledge Discovery 2012: 122-143
- [p3]Anton Dries, Siegfried Nijssen, Luc De Raedt: BiQL: A Query Language for Analyzing Information Networks. Bisociative Knowledge Discovery 2012: 147-165
- [e11]Luc De Raedt, Christian Bessière, Didier Dubois, Patrick Doherty, Paolo Frasconi, Fredrik Heintz, Peter J. F. Lucas (Eds.): ECAI 2012 - 20th European Conference on Artificial Intelligence. Including Prestigious Applications of Artificial Intelligence (PAIS-2012) System Demonstrations Track, Montpellier, France, August 27-31 , 2012. Frontiers in Artificial Intelligence and Applications 242, IOS Press 2012, ISBN 978-1-61499-097-0
- [i10]Daan Fierens, Guy Van den Broeck, Ingo Thon, Bernd Gutmann, Luc De Raedt: Inference in Probabilistic Logic Programs using Weighted CNF's. CoRR abs/1202.3719 (2012)
- [i9]Paolo Frasconi, Fabrizio Costa, Luc De Raedt, Kurt De Grave: kLog: A Language for Logical and Relational Learning with Kernels. CoRR abs/1205.3981 (2012)
- [i8]Angelika Kimmig, Guy Van den Broeck, Luc De Raedt: Algebraic Model Counting. CoRR abs/1211.4475 (2012)
- 2011
- [j43]Tias Guns, Siegfried Nijssen, Luc De Raedt: Itemset mining: A constraint programming perspective. Artif. Intell. 175(12-13): 1951-1983 (2011)
- [j42]Ingo Thon, Niels Landwehr, Luc De Raedt: Stochastic relational processes: Efficient inference and applications. Machine Learning 82(2): 239-272 (2011)
- [j41]Hendrik Blockeel, Karsten M. Borgwardt, Luc De Raedt, Pedro Domingos, Kristian Kersting, Xifeng Yan: Guest editorial to the special issue on inductive logic programming, mining and learning in graphs and statistical relational learning. Machine Learning 83(2): 133-135 (2011)
- [j40]Leander Schietgat, Fabrizio Costa, Jan Ramon, Luc De Raedt: Effective feature construction by maximum common subgraph sampling. Machine Learning 83(2): 137-161 (2011)
- [j39]Angelika Kimmig, Bart Demoen, Luc De Raedt, Vítor Santos Costa, Ricardo Rocha: On the implementation of the probabilistic logic programming language ProbLog. TPLP 11(2-3): 235-262 (2011)
- [j38]Bernd Gutmann, Ingo Thon, Angelika Kimmig, Maurice Bruynooghe, Luc De Raedt: The magic of logical inference in probabilistic programming. TPLP 11(4-5): 663-680 (2011)
- [c127]Angelika Kimmig, Guy Van den Broeck, Luc De Raedt: An Algebraic Prolog for Reasoning about Possible Worlds. AAAI 2011
- [c126]Tias Guns, Siegfried Nijssen, Albrecht Zimmermann, Luc De Raedt: Declarative Heuristic Search for Pattern Set Mining. ICDM Workshops 2011: 1104-1111
- [c125]Guy Van den Broeck, Nima Taghipour, Wannes Meert, Jesse Davis, Luc De Raedt: Lifted Probabilistic Inference by First-Order Knowledge Compilation. IJCAI 2011: 2178-2185
- [c124]Parisa KordJamshidi, Paolo Frasconi, Martijn van Otterlo, Marie-Francine Moens, Luc De Raedt: Relational Learning for Spatial Relation Extraction from Natural Language. ILP 2011: 204-220
- [c123]Mathias Verbeke, Paolo Frasconi, Vincent Van Asch, Roser Morante, Walter Daelemans, Luc De Raedt: Kernel-Based Logical and Relational Learning with kLog for Hedge Cue Detection. ILP 2011: 347-357
- [c122]Luc De Raedt, Siegfried Nijssen: Towards Programming Languages for Machine Learning and Data Mining (Extended Abstract). ISMIS 2011: 25-32
- [c121]Tias Guns, Siegfried Nijssen, Luc De Raedt: Evaluating Pattern Set Mining Strategies in a Constraint Programming Framework. PAKDD (2) 2011: 382-394
- [c120]Bernd Gutmann, Ingo Thon, Luc De Raedt: Learning the Parameters of Probabilistic Logic Programs from Interpretations. ECML/PKDD (1) 2011: 581-596
- [c119]Daan Fierens, Guy Van den Broeck, Ingo Thon, Bernd Gutmann, Luc De Raedt: Inference in Probabilistic Logic Programs using Weighted CNF's. UAI 2011: 211-220
- [i7]Bernd Gutmann, Ingo Thon, Angelika Kimmig, Maurice Bruynooghe, Luc De Raedt: The Magic of Logical Inference in Probabilistic Programming. CoRR abs/1107.5152 (2011)
- [i6]Luc De Raedt, Kristian Kersting, Tapani Raiko: Logical Hidden Markov Models. CoRR abs/1109.2148 (2011)
- [i5]Luc De Raedt, Siegfried Nijssen, Barry O'Sullivan, Pascal Van Hentenryck: Constraint Programming meets Machine Learning and Data Mining (Dagstuhl Seminar 11201). Dagstuhl Reports 1(5): 61-83 (2011)
- 2010
- [j37]Niels Landwehr, Andrea Passerini, Luc De Raedt, Paolo Frasconi: Fast learning of relational kernels. Machine Learning 78(3): 305-342 (2010)
- [j36]Anton Dries, Luc De Raedt, Siegfried Nijssen: Mining Predictive k-CNF Expressions. IEEE Trans. Knowl. Data Eng. 22(5): 743-748 (2010)
- [c118]Guy Van den Broeck, Ingo Thon, Martijn van Otterlo, Luc De Raedt: DTProbLog: A Decision-Theoretic Probabilistic Prolog. AAAI 2010
- [c117]Luc De Raedt, Tias Guns, Siegfried Nijssen: Constraint Programming for Data Mining and Machine Learning. AAAI 2010
- [c116]Maurice Bruynooghe, Theofrastos Mantadelis, Angelika Kimmig, Bernd Gutmann, Joost Vennekens, Gerda Janssens, Luc De Raedt: ProbLog Technology for Inference in a Probabilistic First Order Logic. ECAI 2010: 719-724
- [c115]Laura Antanas, Martijn van Otterlo, José Oramas M., Tinne Tuytelaars, Luc De Raedt: Not Far Away from Home: A Relational Distance-Based Approach to Understanding Images of Houses. ILP 2010: 22-29
- [c114]
- [c113]Bernd Gutmann, Manfred Jaeger, Luc De Raedt: Extending ProbLog with Continuous Distributions. ILP 2010: 76-91
- [p2]Luc De Raedt: About Knowledge and Inference in Logical and Relational Learning. Advances in Machine Learning II 2010: 143-153
- [e10]Luc De Raedt (Ed.): Inductive Logic Programming, 19th International Conference, ILP 2009, Leuven, Belgium, July 02-04, 2009. Revised Papers. Lecture Notes in Computer Science 5989, Springer 2010, ISBN 978-3-642-13839-3
- [r4]
- [r3]
- [r2]
- [r1]Luc De Raedt, Kristian Kersting: Statistical Relational Learning. Encyclopedia of Machine Learning 2010: 916-924
- [i4]Angelika Kimmig, Bart Demoen, Luc De Raedt, Vítor Santos Costa, Ricardo Rocha: On the Implementation of the Probabilistic Logic Programming Language ProbLog. CoRR abs/1006.4442 (2010)
2000 – 2009
- 2009
- [j35]Albrecht Zimmermann, Luc De Raedt: Cluster-grouping: from subgroup discovery to clustering. Machine Learning 77(1): 125-159 (2009)
- [j34]Luc De Raedt, Jan Ramon: Deriving distance metrics from generality relations. Pattern Recognition Letters 30(3): 187-191 (2009)
- [c112]Anton Dries, Siegfried Nijssen, Luc De Raedt: A query language for analyzing networks. CIKM 2009: 485-494
- [c111]
- [c110]
- [c109]
- [c108]
- [c107]
- [c106]Siegfried Nijssen, Tias Guns, Luc De Raedt: Correlated itemset mining in ROC space: a constraint programming approach. KDD 2009: 647-656
- [c105]
- 2008
- [b1]Luc De Raedt: Logical and relational learning. Cognitive Technologies, Springer 2008, ISBN 978-3-540-20040-6, pp. I-XV, 1-387
- [j33]Ulrich Rückert, Luc De Raedt: An experimental evaluation of simplicity in rule learning. Artif. Intell. 172(1): 19-28 (2008)
- [j32]Niels Landwehr, Bernd Gutmann, Ingo Thon, Luc De Raedt, Matthai Philipose: Relational Transformation-based Tagging for Activity Recognition. Fundam. Inform. 89(1): 111-129 (2008)
- [j31]Luc De Raedt, Kristian Kersting, Angelika Kimmig, Kate Revoredo, Hannu Toivonen: Compressing probabilistic Prolog programs. Machine Learning 70(2-3): 151-168 (2008)
- [c104]Luc De Raedt, Barbara Hammer, Pascal Hitzler, Wolfgang Maass: 08041 Summary -- Recurrent Neural Networks - Models, Capacities, and Applications. Recurrent Neural Networks 2008
- [c103]Luc De Raedt, Barbara Hammer, Pascal Hitzler, Wolfgang Maass: 08041 Abstracts Collection -- Recurrent Neural Networks - Models, Capacities, and Applications. Recurrent Neural Networks 2008
- [c102]Kurt De Grave, Jan Ramon, Luc De Raedt: Active Learning for High Throughput Screening. Discovery Science 2008: 185-196
- [c101]Angelika Kimmig, Vítor Santos Costa, Ricardo Rocha, Bart Demoen, Luc De Raedt: On the Efficient Execution of ProbLog Programs. ICLP 2008: 175-189
- [c100]Luc De Raedt, Kristian Kersting: Probabilistic Inductive Logic Programming. Probabilistic Inductive Logic Programming 2008: 1-27
- [c99]Kristian Kersting, Luc De Raedt, Bernd Gutmann, Andreas Karwath, Niels Landwehr: Relational Sequence Learning. Probabilistic Inductive Logic Programming 2008: 28-55
- [c98]Kristian Kersting, Luc De Raedt: Basic Principles of Learning Bayesian Logic Programs. Probabilistic Inductive Logic Programming 2008: 189-221
- [c97]Luc De Raedt, Tias Guns, Siegfried Nijssen: Constraint programming for itemset mining. KDD 2008: 204-212
- [c96]Bernd Gutmann, Angelika Kimmig, Kristian Kersting, Luc De Raedt: Parameter Learning in Probabilistic Databases: A Least Squares Approach. ECML/PKDD (1) 2008: 473-488
- [c95]Ingo Thon, Niels Landwehr, Luc De Raedt: A Simple Model for Sequences of Relational State Descriptions. ECML/PKDD (2) 2008: 506-521
- [c94]
- [c93]Luc De Raedt: Logic, Probability and Learning, or an Introduction to Statistical Relational Learning. SBIA 2008: 5
- [e9]Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Kristian Kersting, Stephen Muggleton (Eds.): Probabilistic, Logical and Relational Learning - A Further Synthesis, 15.04. - 20.04.2007. Dagstuhl Seminar Proceedings 07161, Internationales Begegnungs- und Forschungszentrum fuer Informatik (IBFI), Schloss Dagstuhl, Germany 2008
- [e8]Luc De Raedt, Barbara Hammer, Pascal Hitzler, Wolfgang Maass (Eds.): Recurrent Neural Networks - Models, Capacities, and Applications, 20.01. - 25.01.2008. Dagstuhl Seminar Proceedings 08041, Internationales Begegnungs- und Forschungszentrum fuer Informatik (IBFI), Schloss Dagstuhl, Germany 2008
- [e7]Luc De Raedt, Paolo Frasconi, Kristian Kersting, Stephen Muggleton (Eds.): Probabilistic Inductive Logic Programming - Theory and Applications. Lecture Notes in Computer Science 4911, Springer 2008, ISBN 978-3-540-78651-1
- 2007
- [j30]Tayfun Gürel, Luc De Raedt, Stefan Rotter: Ranking neurons for mining structure-activity relations in biological neural networks: NeuronRank. Neurocomputing 70(10-12): 1897-1901 (2007)
- [j29]Niels Landwehr, Kristian Kersting, Luc De Raedt: Integrating Naïve Bayes and FOIL. Journal of Machine Learning Research 8: 481-507 (2007)
- [c92]Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Kristian Kersting, Stephen Muggleton: 07161 Abstracts Collection -- Probabilistic, Logical and Relational Learning - A Further Synthesis. Probabilistic, Logical and Relational Learning - A Further Synthesis 2007
- [c91]Angelika Kimmig, Luc De Raedt, Hannu Toivonen: Probabilistic Explanation Based Learning. ECML 2007: 176-187
- [c90]Gemma C. Garriga, Roni Khardon, Luc De Raedt: On Mining Closed Sets in Multi-Relational Data. IJCAI 2007: 804-809
- [c89]
- [c88]Luc De Raedt: Statistical Relational Learning - A Logical Approach (Abstract of Invited Talk). NeSy 2007
- [c87]Luc De Raedt, Angelika Kimmig, Hannu Toivonen: ProbLog: A Probabilistic Prolog and Its Application in Link Discovery. IJCAI 2007: 2462-2467
- [c86]Tayfun Gürel, Ulrich Egert, Steffen Kandler, Luc De Raedt, Stefan Rotter: Predicting Spike Activity in Neuronal Cultures. IJCNN 2007: 2942-2947
- [c85]
- [c84]
- [p1]Tayfun Gürel, Luc De Raedt, Stefan Rotter: Mining Structure-Activity Relations in Biological Neural Networks using NeuronRank. Perspectives of Neural-Symbolic Integration 2007: 49-65
- 2006
- [j28]Kristian Kersting, Luc De Raedt, Tapani Raiko: Logical Hidden Markov Models. J. Artif. Intell. Res. (JAIR) 25: 425-456 (2006)
- [j27]Andrea Passerini, Paolo Frasconi, Luc De Raedt: Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting. Journal of Machine Learning Research 7: 307-342 (2006)
- [j26]Rolf Backofen, Hans-Gunther Borrmann, Werner Deck, Andreas Dedner, Luc De Raedt, Klaus Desch, Markus Diesmann, Martin Geier, Andreas Greiner, Wolfgang R. Hess, Josef Honerkamp, Stefan Jankowski, Ingo Krossing, Andreas W. Liehr, Andreas Karwath, Robert Klöfkorn, Raphaël Pesché, Tobias C. Potjans, Michael C. Röttger, Lars Schmidt-Thieme, Gerhard Schneider, Björn Voß, Bernd Wiebelt, Peter Wienemann, Volker-Henning Winterer: A Bottom-up approach to Grid-Computing at a University: the Black-Forest-Grid Initiative. Praxis der Informationsverarbeitung und Kommunikation 29(2): 81-87 (2006)
- [c83]Niels Landwehr, Andrea Passerini, Luc De Raedt, Paolo Frasconi: kFOIL: Learning Simple Relational Kernels. AAAI 2006: 389-394
- [c82]Luc De Raedt, Kristian Kersting, Angelika Kimmig, Kate Revoredo, Hannu Toivonen: Revising Probabilistic Prolog Programs. ILP 2006: 30-33
- [c81]
- [c80]Alexandru Cocora, Kristian Kersting, Christian Plagemann, Wolfram Burgard, Luc De Raedt: Learning Relational Navigation Policies. IROS 2006: 2792-2797
- [c79]Jérémy Besson, Céline Robardet, Luc De Raedt, Jean-François Boulicaut: Mining Bi-sets in Numerical Data. KDID 2006: 11-23
- [c78]Siegfried Nijssen, Luc De Raedt: IQL: A Proposal for an Inductive Query Language. KDID 2006: 189-207
- [c77]Björn Bringmann, Albrecht Zimmermann, Luc De Raedt, Siegfried Nijssen: Don't Be Afraid of Simpler Patterns. PKDD 2006: 55-66
- [e6]Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Stephen Muggleton (Eds.): Probabilistic, Logical and Relational Learning - Towards a Synthesis, 30. January - 4. February 2005. Dagstuhl Seminar Proceedings 05051, Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, Germany 2006
- 2005
- [j25]Takashi Washio, Luc De Raedt, Joost N. Kok: Advances in Mining Graphs, Trees and Sequences. Fundam. Inform. 66(1-2) (2005)
- [c76]Luc De Raedt, Kristian Kersting, Sunna Torge: Towards Learning Stochastic Logic Programs from Proof-Banks. AAAI 2005: 752-757
- [c75]Niels Landwehr, Kristian Kersting, Luc De Raedt: nFOIL: Integrating Naïve Bayes and FOIL. AAAI 2005: 795-800
- [c74]Andrea Passerini, Paolo Frasconi, Luc De Raedt: Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting. Probabilistic, Logical and Relational Learning 2005
- [c73]Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Stephen Muggleton: 05051 Executive Summary - Probabilistic, Logical and Relational Learning - Towards a Synthesis. Probabilistic, Logical and Relational Learning 2005
- [c72]Luc De Raedt, Thomas G. Dietterich, Lise Getoor, Stephen Muggleton: 05051 Abstracts Collection - Probabilistic, Logical and Relational Learning - Towards a Synthesis. Probabilistic, Logical and Relational Learning 2005
- [c71]Christian Stolle, Andreas Karwath, Luc De Raedt: CLASSIC'CL: An Integrated ILP System. Discovery Science 2005: 354-362
- [c70]Luc De Raedt: Statistical Relational Learning: An Inductive Logic Programming Perspective. PKDD 2005: 3-5
- [e5]Jean-François Boulicaut, Luc De Raedt, Heikki Mannila (Eds.): Constraint-Based Mining and Inductive Databases, European Workshop on Inductive Databases and Constraint Based Mining, Hinterzarten, Germany, March 11-13, 2004, Revised Selected Papers. Lecture Notes in Computer Science 3848, Springer 2005, ISBN 3-540-31331-1
- [e4]Luc De Raedt, Stefan Wrobel (Eds.): Machine Learning, Proceedings of the Twenty-Second International Conference (ICML 2005), Bonn, Germany, August 7-11, 2005. ACM International Conference Proceeding Series 119, ACM 2005, ISBN 1-59593-180-5
- 2004
- [j24]Christoph Helma, Tobias Cramer, Stefan Kramer, Luc De Raedt: Data Mining and Machine Learning Techniques for the Identification of Mutagenicity Inducing Substructures and Structure Activity Relationships of Noncongeneric Compounds. Journal of Chemical Information and Modeling 44(4): 1402-1411 (2004)
- [c69]
- [c68]Luc De Raedt: Towards Query Evaluation in Inductive Databases Using Version Spaces. Database Support for Data Mining Applications 2004: 117-134
- [c67]Sau Dan Lee, Luc De Raedt: Constraint Based Mining of First Order Sequences in SeqLog. Database Support for Data Mining Applications 2004: 154-173
- [c66]Albrecht Zimmermann, Luc De Raedt: Inductive Querying for Discovering Subgroups and Clusters. Constraint-Based Mining and Inductive Databases 2004: 380-399
- [c65]
- [c64]Albrecht Zimmermann, Luc De Raedt: CorClass: Correlated Association Rule Mining for Classification. Discovery Science 2004: 60-72
- [c63]Albrecht Zimmermann, Luc De Raedt: Cluster-Grouping: From Subgroup Discovery to Clustering. ECML 2004: 575-577
- [c62]
- [c61]Kristian Kersting, Luc De Raedt: Logical Markov Decision Programs and the Convergence of Logical TD(lambda). ILP 2004: 180-197
- [c60]Sau Dan Lee, Luc De Raedt: An Efficient Algorithm for Mining String Databases Under Constraints. KDID 2004: 108-129
- [c59]
- [c58]Johannes Fischer, Luc De Raedt: Towards Optimizing Conjunctive Inductive Queries. PAKDD 2004: 625-637
- 2003
- [j23]Luc De Raedt, Kristian Kersting: Probabilistic logic learning. SIGKDD Explorations 5(1): 31-48 (2003)
- [j22]Saso Dzeroski, Luc De Raedt: Multi-relational data mining: the current frontiers. SIGKDD Explorations 5(1): 100-101 (2003)
- [j21]Saso Dzeroski, Luc De Raedt, Stefan Wrobel: Multirelational data mining 2003: workshop report. SIGKDD Explorations 5(2): 200-202 (2003)
- [c57]
- [c56]
- [c55]
- [c54]Kristian Kersting, Tapani Raiko, Stefan Kramer, Luc De Raedt: Towards Discovering Structural Signatures of Protein Folds Based on Logical Hidden Markov Models. Pacific Symposium on Biocomputing 2003: 192-203
- 2002
- [j20]
- [j19]Saso Dzeroski, Luc De Raedt: Multi-Relational Data Mining: a Workshop Report. SIGKDD Explorations 4(2): 122-124 (2002)
- [c53]Luc De Raedt: Data Mining as Constraint Logic Programming. Computational Logic: Logic Programming and Beyond 2002: 526-547
- [c52]Ulrich Rückert, Stefan Kramer, Luc De Raedt: Phase Transitions and Stochastic Local Search in k-Term DNF Learning. ECML 2002: 405-417
- [c51]Luc De Raedt, Manfred Jaeger, Sau Dan Lee, Heikki Mannila: A Theory of Inductive Query Answering. ICDM 2002: 123-130
- [c50]Sau Dan Lee, Luc De Raedt: Constraint Based Mining of First Order Sequences in SeqLog. KDID 2002: 76-92
- [c49]Kristian Kersting, Tapani Raiko, Luc De Raedt: Logical Hidden Markov Models (Extendes abstract). Probabilistic Graphical Models 2002
- 2001
- [j18]Saso Dzeroski, Luc De Raedt, Kurt Driessens: Relational Reinforcement Learning. Machine Learning 43(1/2): 7-52 (2001)
- [c48]Wim Van Laer, Luc De Raedt: How to Upgrade Propositional Learners to First Order Logic: A Case Study. Machine Learning and Its Applications 2001: 102-126
- [c47]Stefan Kramer, Luc De Raedt: Feature Construction with Version Spaces for Biochemical Applications. ICML 2001: 258-265
- [c46]Luc De Raedt, Stefan Kramer: The Levelwise Version Space Algorithm and its Application to Molecular Fragment Finding. IJCAI 2001: 853-862
- [c45]
- [c44]Kristian Kersting, Luc De Raedt: Towards Combining Inductive Logic Programming with Bayesian Networks. ILP 2001: 118-131
- [c43]Stefan Kramer, Luc De Raedt, Christoph Helma: Molecular feature mining in HIV data. KDD 2001: 136-143
- [e3]Luc De Raedt, Peter A. Flach (Eds.): Machine Learning: EMCL 2001, 12th European Conference on Machine Learning, Freiburg, Germany, September 5-7, 2001, Proceedings. Lecture Notes in Computer Science 2167, Springer 2001, ISBN 3-540-42536-5
- [e2]Luc De Raedt, Arno Siebes (Eds.): Principles of Data Mining and Knowledge Discovery, 5th European Conference, PKDD 2001, Freiburg, Germany, September 3-5, 2001, Proceedings. Lecture Notes in Computer Science 2168, Springer 2001, ISBN 3-540-42534-9
- [i3]
- 2000
- [j17]Luc De Raedt, Johannes A. La Poutré, Floor Verdenius: AI Research in the Benelux - Guest Editorial. AI Commun. 13(1): 1-2 (2000)
- [j16]
- [c42]
- [c41]
- [i2]Hendrik Blockeel, Luc De Raedt, Jan Ramon: Top-down induction of clustering trees. CoRR cs.LG/0011032 (2000)
- [i1]Hendrik Blockeel, Luc De Raedt, Nico Jacobs, Bart Demoen: Scaling Up Inductive Logic Programming by Learning from Interpretations. CoRR cs.LG/0011044 (2000)
1990 – 1999
- 1999
- [j15]Hendrik Blockeel, Luc De Raedt, Nico Jacobs, Bart Demoen: Scaling Up Inductive Logic Programming by Learning from Interpretations. Data Min. Knowl. Discov. 3(1): 59-93 (1999)
- [c40]Shan-Hwei Nienhuys-Cheng, Wim Van Laer, Jan Ramon, Luc De Raedt: Generalizing Refinement Operators to Learn Prenex Conjunctive Normal Forms. ILP 1999: 245-256
- [c39]
- [c38]
- [c37]Luc De Raedt, Hendrik Blockeel: Relational Learning and Inductive Logic Programming Made Easy Abstract of Tutorial. PKDD 1999: 590
- 1998
- [j14]Hendrik Blockeel, Luc De Raedt: Isidd: An Interactive System for Inductive Database Design. Applied Artificial Intelligence 12(5): 385-420 (1998)
- [j13]Hendrik Blockeel, Luc De Raedt: Top-Down Induction of First-Order Logical Decision Trees. Artif. Intell. 101(1-2): 285-297 (1998)
- [c36]
- [c35]
- [c34]Saso Dzeroski, Luc De Raedt, Hendrik Blockeel: Relational Reinforcement Learning. ICML 1998: 136-143
- [c33]Luc De Raedt: Attribute-Value Learning Versus Inductive Logic Programming: The Missing Links (Extended Abstract). ILP 1998: 1-8
- [c32]
- [c31]Nico Jacobs, Kurt Driessens, Luc De Raedt: Using ILP-Systems for Verification and Validation of Multi-agent Systems. ILP 1998: 145-154
- [c30]Kurt Driessens, Nico Jacobs, Nathalie Cossement, Patrick Monsieurs, Luc De Raedt: Inductive Verification and Validation of the KULRoT RoboCup Team. RoboCup 1998: 193-206
- 1997
- [j12]
- [j11]Luc De Raedt: Artificial Intelligence in Belgium and the BeNeLux: Past and Future. AI Commun. 10(3-4): 201-202 (1997)
- [j10]
- [c29]Luc De Raedt, Peter Idestam-Almquist, Gunther Sablon: Theta-Subsumption for Structural Matching. ECML 1997: 73-84
- [c28]
- [c27]
- [c26]
- [c25]
- [c24]Wim Van Laer, Luc De Raedt, Saso Dzeroski: On Multi-class Problems and Discretization in Inductive Logic Programming. ISMIS 1997: 277-286
- 1996
- [j9]Luc De Raedt, Nada Lavrac: Multiple Predicate Learning in Two Inductive Logic Programming Settings. Logic Journal of the IGPL 4(2): 227-254 (1996)
- [c23]Erika Van Baelen, Luc De Raedt: Analysis and Prediction of Piano Performances Using Inductive Logic Programming. Inductive Logic Programming Workshop 1996: 55-71
- [c22]Hendrik Blockeel, Luc De Raedt: Relational Knowledge Discovery in Databases. Inductive Logic Programming Workshop 1996: 199-211
- [c21]
- [c20]
- [c19]
- 1995
- [j8]Nada Lavrac, Luc De Raedt: Inductive Logic Programming: A Survey of European Research. AI Commun. 8(1): 3-19 (1995)
- [j7]Hilde Adé, Luc De Raedt, Maurice Bruynooghe: Declarative Bias for Specific-to-General ILP Systems. Machine Learning 20(1-2): 119-154 (1995)
- [c18]
- [c17]Gunther Sablon, Luc De Raedt: Forgetting and Compacting data in Concept Learning. IJCAI 1995: 432-438
- 1994
- [j6]Gunther Sablon, Luc De Raedt, Maurice Bruynooghe: Iterative Versionspaces. Artif. Intell. 69(1-2): 393-409 (1994)
- [j5]Luc De Raedt, Saso Dzeroski: First-Order jk-Clausal Theories are PAC-Learnable. Artif. Intell. 70(1-2): 375-392 (1994)
- [j4]Stephen Muggleton, Luc De Raedt: Inductive Logic Programming: Theory and Methods. J. Log. Program. 19/20: 629-679 (1994)
- [c16]
- [c15]Wim Van Laer, Luc Dehaspe, Luc De Raedt: Applications of a Logical Discovery Engine. KDD Workshop 1994: 263-274
- [e1]Francesco Bergadano, Luc De Raedt (Eds.): Machine Learning: ECML-94, European Conference on Machine Learning, Catania, Italy, April 6-8, 1994, Proceedings. Lecture Notes in Computer Science 784, Springer 1994, ISBN 3-540-57868-4
- 1993
- [c14]
- [c13]
- [c12]
- [c11]
- 1992
- [j3]Luc De Raedt, Maurice Bruynooghe: Belief Updating from Integrity Constraints and Queries. Artif. Intell. 53(2-3): 291-307 (1992)
- [j2]Luc De Raedt, Johan Feyaerts, Maurice Bruynooghe: Acquiring object-knowledge. J. Exp. Theor. Artif. Intell. 4(3): 213-232 (1992)
- [j1]Luc De Raedt, Maurice Bruynooghe: Interactive Concept-Learning and Constructive Induction by Analogy. Machine Learning 8: 107-150 (1992)
- [c10]Hilde Adé, Luc De Raedt, Maurice Bruynooghe: Inverse Resolution in an Integrated Inductive-Deductive Learning System. ECAI 1992: 456-457
- 1991
- [c9]Luc De Raedt, Johan Feyaerts, Maurice Bruynooghe: Acquiring Object-Knowledge for Learning Systems. EWSL 1991: 245-264
- [c8]
- [c7]Luc De Raedt, Maurice Bruynooghe, Bern Martens: Integrity Constraints and Interactive Concept-Learning. ML 1991: 394-398
- 1990
- [c6]Luc De Raedt, Maurice Bruynooghe: On Negation and Three-Valued Logic in Interactive Concept-Learning. ECAI 1990: 207-212
1980 – 1989
- 1989
- [c5]Gunther Sablon, Luc De Raedt, Maurice Bruynooghe: Generalizing Multiple Examples in Explanation Based Learning. AII 1989: 177-183
- [c4]
- [c3]Maurice Bruynooghe, Luc De Raedt, Danny De Schreye: Explanation Based Program Transformation. IJCAI 1989: 407-412
- [c2]
- 1988
- [c1]Luc De Raedt, Maurice Bruynooghe: On Interactive Concept-Learning and Assimilation. EWSL 1988: 167-176
Coauthor Index
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last updated on 2013-10-02 11:19 CEST by the dblp team