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Note: Links lead to the DBLP on the Web. Hendrik Blockeel Daan Fierens , Hendrik Blockeel, Maurice Bruynooghe , Jan Ramon : Logical Bayesian Networks and Their Relation to Other Probabilistic Logical Models. BNAIC 2005 : 343-344 Daan Fierens , Jan Ramon , Hendrik Blockeel, Maurice Bruynooghe : A Comparison of Approaches for Learning Probability Trees. ECML 2005 : 556-563 Jan Struyf , Saso Dzeroski , Hendrik Blockeel, Amanda Clare : Hierarchical Multi-classification with Predictive Clustering Trees in Functional Genomics. EPIA 2005 : 272-283 Hendrik Blockeel, David Page , Ashwin Srinivasan : Multi-instance tree learning. ICML 2005 : 57-64 Daan Fierens , Hendrik Blockeel, Maurice Bruynooghe , Jan Ramon : Logical Bayesian Networks and Their Relation to Other Probabilistic Logical Models. ILP 2005 : 121-135 Werner Uwents , Hendrik Blockeel: Classifying Relational Data with Neural Networks. ILP 2005 : 384-396 Hendrik Blockeel: Experiment Databases: A Novel Methodology for Experimental Research. KDID 2005 : 72-85 Hendrik Blockeel, Saso Dzeroski : Multi-Relational Data Mining 2005: workshop report. SIGKDD Explorations 7 (2): 126-128 (2005) Celine Vens , Anneleen Van Assche , Hendrik Blockeel, Saso Dzeroski : First Order Random Forests with Complex Aggregates. ILP 2004 : 323-340 Hendrik Blockeel, Saso Dzeroski , Boris Kompare , Stefan Kramer , Bernhard Pfahringer , Wim Van Laer : Experiments In Predicting Biodegradability. Applied Artificial Intelligence 18 (2): 157-181 (2004) Jan Struyf , Jan Ramon , Maurice Bruynooghe , Sofie Verbaeten , Hendrik Blockeel: Compact Representation of Knowledge Bases in Inductive Logic Programming. Machine Learning 57 (3): 305-333 (2004) Saso Dzeroski , Hendrik Blockeel: Multi-relational data mining 2004: workshop report. SIGKDD Explorations 6 (2): 140-141 (2004) Nada Lavrac , Dragan Gamberger , Ljupco Todorovski , Hendrik Blockeel: Machine Learning: ECML 2003, 14th European Conference on Machine Learning, Cavtat-Dubrovnik, Croatia, September 22-26, 2003, Proceedings Springer 2003 Nada Lavrac , Dragan Gamberger , Hendrik Blockeel, Ljupco Todorovski : Knowledge Discovery in Databases: PKDD 2003, 7th European Conference on Principles and Practice of Knowledge Discovery in Databases, Cavtat-Dubrovnik, Croatia, September 22-26, 2003, Proceedings Springer 2003 Raymond Kosala , Maurice Bruynooghe , Jan Van den Bussche , Hendrik Blockeel: Information Extraction from Web Documents Based on Local Unranked Tree Automaton Inference. IJCAI 2003 : 403-408 Jan Struyf , Hendrik Blockeel: Query Optimization in Inductive Logic Programming by Reordering Literals. ILP 2003 : 329-346 Vítor Santos Costa , Ashwin Srinivasan , Rui Camacho , Hendrik Blockeel, Bart Demoen , Gerda Janssens , Jan Struyf , Henk Vandecasteele , Wim Van Laer : Query Transformations for Improving the Efficiency of ILP Systems. Journal of Machine Learning Research 4 : 465-491 (2003) Hendrik Blockeel, Michèle Sebag : Scalability and efficiency in multi-relational data mining. SIGKDD Explorations 5 (1): 17-30 (2003) Ljupco Todorovski , Hendrik Blockeel, Saso Dzeroski : Ranking with Predictive Clustering Trees. ECML 2002 : 444-455 Jan Struyf , Jan Ramon , Hendrik Blockeel: Compact Representation of Knowledge Bases in ILP. ILP 2002 : 254-269 Raymond Kosala , Jan Van den Bussche , Maurice Bruynooghe , Hendrik Blockeel: Information Extraction in Structured Documents Using Tree Automata Induction. PKDD 2002 : 299-310 Hendrik Blockeel, Jan Struyf : Deriving biased classifiers for better ROC performance. Informatica (Slovenia) 26 (1): (2002) Hendrik Blockeel, Luc Dehaspe , Bart Demoen , Gerda Janssens , Jan Ramon , Henk Vandecasteele : Improving the Efficiency of Inductive Logic Programming Through the Use of Query Packs. J. Artif. Intell. Res. (JAIR) 16 : 135-166 (2002) Hendrik Blockeel, Jan Struyf : Efficient Algorithms for Decision Tree Cross-validation. Journal of Machine Learning Research 3 : 621-650 (2002) Kurt Driessens , Jan Ramon , Hendrik Blockeel: Speeding Up Relational Reinforcement Learning through the Use of an Incremental First Order Decision Tree Learner. ECML 2001 : 97-108 Hendrik Blockeel, Jan Struyf : Efficient algorithms for decision tree cross-validation. ICML 2001 : 11-18 Jan Struyf , Hendrik Blockeel: Efficient Cross-Validation in ILP. ILP 2001 : 228-239 Nico Jacobs , Hendrik Blockeel: From Shell Logs to Shell Scripts. ILP 2001 : 80-90 Hendrik Blockeel, Johannes Fürnkranz , Alexia Prskawetz , Francesco Billari : Detecting Temporal Change in Event Sequences: An Application to Demographic Data. PKDD 2001 : 29-41 Nico Jacobs , Hendrik Blockeel: The Learning Shell: Automated Macro Construction. User Modeling 2001 : 34-43 Hendrik Blockeel, Jan Struyf : Efficient algorithms for decision tree cross-validation CoRR cs.LG/0110036 : (2001) Jan Ramon , Tom Francis , Hendrik Blockeel: Learning a Go Heuristic with TILDE. Computers and Games 2000 : 151-169 Hendrik Blockeel, Luc Dehaspe , Bart Demoen , Gerda Janssens , Jan Ramon , Henk Vandecasteele : Executing Query Packs in ILP. ILP 2000 : 60-77 Hendrik Blockeel, Bart Demoen , Gerda Janssens , Henk Vandecasteele , Wim Van Laer : Two Advanced Transormations for Improving the Efficiency of an ILP system. ILP Work-in-progress reports 2000 Arno J. Knobbe , Arno Siebes , Hendrik Blockeel, Danïel van der Wallen : Multi-Relational Data Mining, Using UML for ILP. PKDD 2000 : 1-12 Hendrik Blockeel, Luc De Raedt , Jan Ramon : Top-down induction of clustering trees CoRR cs.LG/0011032 : (2000) Raymond Kosala , Hendrik Blockeel: Web Mining Research: A Survey CoRR cs.LG/0011033 : (2000) Hendrik Blockeel, Luc De Raedt , Nico Jacobs , Bart Demoen : Scaling Up Inductive Logic Programming by Learning from Interpretations CoRR cs.LG/0011044 : (2000) Raymond Kosala , Hendrik Blockeel: Web Mining Research: A Survey. SIGKDD Explorations 2 (1): 1-15 (2000) Saso Dzeroski , Hendrik Blockeel, Boris Kompare , Stefan Kramer , Bernhard Pfahringer , Wim Van Laer : Experiments in Predicting Biodegradability. ILP 1999 : 80-91 Hendrik Blockeel, Saso Dzeroski , Jasna Grbovic : Simultaneous Prediction of Mulriple Chemical Parameters of River Water Quality with TILDE. PKDD 1999 : 32-40 Luc De Raedt , Hendrik Blockeel: Relational Learning and Inductive Logic Programming Made Easy Abstract of Tutorial. PKDD 1999 : 590 Hendrik Blockeel: Top-Down Induction of First Order Logical Decision Trees. AI Commun. 12 (1-2): 119-120 (1999) 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) Saso Dzeroski , Luc De Raedt , Hendrik Blockeel: Relational Reinforcement Learning. ICML 1998 : 136-143 Hendrik Blockeel, Luc De Raedt , Jan Ramon : Top-Down Induction of Clustering Trees. ICML 1998 : 55-63 Saso Dzeroski , Luc De Raedt , Hendrik Blockeel: Relational Reinforcement Learning. ILP 1998 : 11-22 Saso Dzeroski , Steffen Schulze-Kremer , Karsten R. Heidtke , Karsten Siems , Dietrich Wettschereck , Hendrik Blockeel: Diterpene Structure Elucidation from 13CNMR Spectra with Inductive Logic Programming. Applied Artificial Intelligence 12 (5): 363-383 (1998) Hendrik Blockeel, Luc De Raedt : Isidd: An Interactive System for Inductive Database Design. Applied Artificial Intelligence 12 (5): 385-420 (1998) Hendrik Blockeel, Luc De Raedt : Top-Down Induction of First-Order Logical Decision Trees. Artif. Intell. 101 (1-2): 285-297 (1998) Luc De Raedt , Hendrik Blockeel: Using Logical Decision Trees for Clustering. ILP 1997 : 133-140 Hendrik Blockeel, Luc De Raedt : Lookahead and Discretization in ILP. ILP 1997 : 77-84 Hendrik Blockeel, Luc De Raedt : Inductive Database Design. ISMIS 1996 : 376-385 Hendrik Blockeel, Luc De Raedt : Relational Knowledge Discovery in Databases. Inductive Logic Programming Workshop 1996 : 199-211 1 [ 46 ] 2 [ 26 ] 3 [ 34 ] [ 40 ] [ 44 ] [ 50 ] [ 53 ] [ 54 ] 4 [ 34 ] [ 40 ] 5 [ 38 ] 6 [ 52 ] 7 [ 38 ] 8 [ 22 ] [ 32 ] 9 [ 11 ] [ 17 ] [ 21 ] [ 22 ] [ 32 ] [ 38 ] 10 [ 30 ] 11 [ 7 ] [ 8 ] [ 10 ] [ 14 ] [ 15 ] [ 36 ] [ 43 ] [ 45 ] [ 46 ] [ 47 ] [ 52 ] 12 [ 50 ] [ 53 ] [ 54 ] 13 [ 23 ] 14 [ 26 ] 15 [ 41 ] [ 42 ] 16 [ 14 ] 17 [ 7 ] 18 [ 11 ] [ 17 ] [ 25 ] [ 27 ] 19 [ 21 ] [ 22 ] [ 32 ] [ 38 ] 20 [ 20 ] 21 [ 15 ] [ 45 ] 22 [ 16 ] [ 18 ] [ 34 ] [ 40 ] 23 [ 15 ] [ 45 ] 24 [ 15 ] [ 21 ] [ 38 ] [ 45 ] 25 [ 41 ] [ 42 ] 26 [ 51 ] 27 [ 15 ] [ 45 ] 28 [ 26 ] 29 [ 1 ] [ 2 ] [ 3 ] [ 4 ] [ 5 ] [ 6 ] [ 8 ] [ 9 ] [ 10 ] [ 11 ] [ 13 ] [ 17 ] [ 19 ] 30 [ 9 ] [ 19 ] [ 22 ] [ 23 ] [ 30 ] [ 32 ] [ 35 ] [ 44 ] [ 50 ] [ 53 ] [ 54 ] 31 [ 7 ] 32 [ 37 ] 33 [ 20 ] 34 [ 7 ] 35 [ 38 ] [ 51 ] 36 [ 24 ] [ 28 ] [ 29 ] [ 31 ] [ 33 ] [ 35 ] [ 38 ] [ 39 ] [ 44 ] [ 52 ] 37 [ 36 ] [ 41 ] [ 42 ] 38 [ 49 ] 39 [ 21 ] [ 22 ] [ 32 ] [ 38 ] 40 [ 46 ] 41 [ 44 ] 42 [ 20 ] 43 [ 7 ]  ©2006 Association for Computing Machinery |
