2012
62Nearly Exact Mining of Frequent Trees in Large Networks. Ashraf M. Kibriya, Jan Ramon. ECML/PKDD (1) 2012, 426-441. Web SearchBibTeXDownload
61An Efficiently Computable Support Measure for Frequent Subgraph Pattern Mining. Yuyi Wang, Jan Ramon. ECML/PKDD (1) 2012, 362-377. Web SearchBibTeXDownload
60Open Problem: Learning Dynamic Network Models from a Static Snapshot. Jan Ramon, Constantin Comendant. Journal of Machine Learning Research - Proceedings Track (23): 45.1-45.3 (2012). Web SearchBibTeXDownload
2011
59Computerized prediction of intensive care unit discharge after cardiac surgery: development and validation of a Gaussian processes model. Geert Meyfroidt, Fabián Güiza, Dominiek Cottem, Wilfried De Becker, Kristien Van Loon, Jean-Marie Aerts, Daniel Berckmans, Jan Ramon, Maurice Bruynooghe, Greet Vanden Berghe. BMC Med. Inf. & Decision Making (11): 64 (2011). Web SearchBibTeXDownload
58Improving the Efficiency of Inductive Logic Programming Through the Use of Query Packs. Hendrik Blockeel, Luc Dehaspe, Bart Demoen, Guy Janssens, Jan Ramon, Henk Vandecasteele. CoRR (abs/1106.1803) (2011). Web SearchBibTeXDownload
57All normalized anti-monotonic overlap graph measures are bounded. Toon Calders, Jan Ramon, Dries Van Dyck. Data Min. Knowl. Discov. (23): 503-548 (2011). Web SearchBibTeXDownload
56Effective feature construction by maximum common subgraph sampling. Leander Schietgat, Fabrizio Costa, Jan Ramon, Luc De Raedt. Machine Learning (83): 137-161 (2011). Web SearchBibTeXDownload
2010
55Frequent subgraph mining in outerplanar graphs. Tamás Horváth, Jan Ramon, Stefan Wrobel. Data Min. Knowl. Discov. (21): 472-508 (2010). Web SearchBibTeXDownload
54Learning with Whom to Communicate Using Relational Reinforcement Learning. Marc Ponsen, Tom Croonenborghs, Karl Tuyls, Jan Ramon, Kurt Driessens, Jaap van den Herik, Eric Postma. Interactive Collaborative Information Systems 2010, 45-63. Web SearchBibTeXDownload
53Prediction of Clinical Conditions after Coronary Bypass Surgery using Dynamic Data Analysis. Kristien Van Loon, Fabián Güiza, Geert Meyfroidt, Jean-Marie Aerts, Jan Ramon, Hendrik Blockeel, Maurice Bruynooghe, Greta Van den Berghe, Daniel Berckmans. J. Medical Systems (34): 229-239 (2010). Web SearchBibTeXDownload
52A comparison of pruning criteria for probability trees. Daan Fierens, Jan Ramon, Hendrik Blockeel, Maurice Bruynooghe. Machine Learning (78): 251-285 (2010). Web SearchBibTeXDownload
51Efficient frequent connected subgraph mining in graphs of bounded tree-width. Tamás Horváth, Jan Ramon. Theor. Comput. Sci. (411): 2784-2797 (2010). Web SearchBibTeXDownload
2009
50Learning with whom to communicate using relational reinforcement learning. Marc J. V. Ponsen, Tom Croonenborghs, Karl Tuyls, Jan Ramon, Kurt Driessens. AAMAS (2) 2009, 1221-1222. Web SearchBibTeXDownload
49Monte-Carlo Tree Search in Poker Using Expected Reward Distributions. Guy Van den Broeck, Kurt Driessens, Jan Ramon. ACML 2009, 367-381. Web SearchBibTeXDownload
48Polynomial-Delay Enumeration of Monotonic Graph Classes. Jan Ramon, Siegfried Nijssen. Journal of Machine Learning Research (10): 907-929 (2009). Web SearchBibTeXDownload
47Handling missing values and censored data in PCA of pharmacological matrices. Jan Ramon, Fabrizio Costa. KDD Workshop on Statistical and Relational Learning in Bioinformatics 2009, 32-34. Web SearchBibTeXDownload
46Dynamic Data Analysis and Data Mining for Prediction of Clinical Stability. Kristien Van Loon, Fabián Güiza, Geert Meyfroidt, Jean-Marie Aerts, Jan Ramon, Hendrik Blockeel, Maurice Bruynooghe, Greet Vanden Berghe, Daniel Berckmans. MIE 2009, 590-594. Web SearchBibTeXDownload
45Deriving distance metrics from generality relations. Luc De Raedt, Jan Ramon. Pattern Recognition Letters (30): 187-191 (2009). Web SearchBibTeXDownload
44StReBio'09: statistical relational learning and mining in bioinformatics. Jan Ramon, Fabrizio Costa, Christophe Costa Floręncio, Joost N. Kok. SIGKDD Explorations (11): 88-89 (2009). Web SearchBibTeXDownload
2008
43Bayes-Relational Learning of Opponent Models from Incomplete Information in No-Limit Poker. Marc J. V. Ponsen, Jan Ramon, Tom Croonenborghs, Kurt Driessens, Karl Tuyls. AAAI 2008, 1485-1486. Web SearchBibTeXDownload
42Learning directed probabilistic logical models: ordering-search versus structure-search. Daan Fierens, Jan Ramon, Maurice Bruynooghe, Hendrik Blockeel. Ann. Math. Artif. Intell. (54): 99-133 (2008). Web SearchBibTeXDownload
41Active Learning for High Throughput Screening. Kurt De Grave, Jan Ramon, Luc De Raedt. Discovery Science 2008, 185-196. Web SearchBibTeXDownload
40An Efficiently Computable Graph-Based Metric for the Classification of Small Molecules. Leander Schietgat, Jan Ramon, Maurice Bruynooghe, Hendrik Blockeel. Discovery Science 2008, 197-209. Web SearchBibTeXDownload
39Using Decision Trees as the Answer Networks in Temporal Difference-Networks. Laura-Andreea Antanas, Kurt Driessens, Jan Ramon, Tom Croonenborghs. ECAI 2008, 847-848. Web SearchBibTeXDownload
38Efficient Frequent Connected Subgraph Mining in Graphs of Bounded Treewidth. Tamás Horváth, Jan Ramon. ECML/PKDD (1) 2008, 520-535. Web SearchBibTeXDownload
37Anti-monotonic Overlap-Graph Support Measures. Toon Calders, Jan Ramon, Dries Van Dyck. ICDM 2008, 73-82. Web SearchBibTeXDownload
36Generalized ordering-search for learning directed probabilistic logical models. Jan Ramon, Tom Croonenborghs, Daan Fierens, Hendrik Blockeel, Maurice Bruynooghe. Machine Learning (70): 169-188 (2008). Web SearchBibTeXDownload
2007
35On Policy Learning in Restricted Policy Spaces. Robby Goetschalckx, Jan Ramon. AAAI 2007, 1858-1859. Web SearchBibTeXDownload
34Mining data from intensive care patients. Jan Ramon, Daan Fierens, Fabián Güiza, Geert Meyfroidt, Hendrik Blockeel, Maurice Bruynooghe, Greet Vanden Berghe. Advanced Engineering Informatics (21): 243-256 (2007). Web SearchBibTeXDownload
33Learning Directed Probabilistic Logical Models: Ordering-Search Versus Structure-Search. Daan Fierens, Jan Ramon, Maurice Bruynooghe, Hendrik Blockeel. ECML 2007, 567-574. Web SearchBibTeXDownload
32Transfer Learning in Reinforcement Learning Problems Through Partial Policy Recycling. Jan Ramon, Kurt Driessens, Tom Croonenborghs. ECML 2007, 699-707. Web SearchBibTeXDownload
31Online Learning and Exploiting Relational Models in Reinforcement Learning. Tom Croonenborghs, Jan Ramon, Hendrik Blockeel, Maurice Bruynooghe. IJCAI 2007, 726-731. Web SearchBibTeXDownload
30Learning Directed Probabilistic Logical Models Using Ordering-Search. Daan Fierens, Jan Ramon, Maurice Bruynooghe, Hendrik Blockeel. ILP 2007, 24. Web SearchBibTeXDownload
29A Polynomial-time Metric for Outerplanar Graphs. Leander Schietgat, Jan Ramon, Maurice Bruynooghe. MLG 2007. Web SearchBibTeXDownload
28General Graph Refinement with Polynomial Delay. Jan Ramon, Siegfried Nijssen. MLG 2007. Web SearchBibTeXDownload
2006
27ReMauve: A Relational Model Tree Learner. Celine Vens, Jan Ramon, Hendrik Blockeel. ILP 2006, 424-438. Web SearchBibTeXDownload
26Generalized Ordering-Search for Learning Directed Probabilistic Logical Models. Jan Ramon, Tom Croonenborghs, Daan Fierens, Hendrik Blockeel, Maurice Bruynooghe. ILP 2006, 40-42. Web SearchBibTeXDownload
25Frequent subgraph mining in outerplanar graphs. Tamás Horváth, Jan Ramon, Stefan Wrobel. KDD 2006, 197-206. Web SearchBibTeXDownload
24Frequent Subgraph Mining in Outerplanar Graphs. Tamás Horváth, Jan Ramon, Stefan Wrobel. LWA 2006, 290-296. Web SearchBibTeXDownload
23Graph kernels and Gaussian processes for relational reinforcement learning. Kurt Driessens, Jan Ramon, Thomas Gärtner. Machine Learning (64): 91-119 (2006). Web SearchBibTeXDownload
22Refining Aggregate Conditions in Relational Learning. Celine Vens, Jan Ramon, Hendrik Blockeel. PKDD 2006, 383-394. Web SearchBibTeXDownload
2005
21Logical Bayesian Networks and Their Relation to Other Probabilistic Logical Models. Daan Fierens, Hendrik Blockeel, Maurice Bruynooghe, Jan Ramon. BNAIC 2005, 343-344. Web SearchBibTeX
20A Comparison of Approaches for Learning Probability Trees. Daan Fierens, Jan Ramon, Hendrik Blockeel, Maurice Bruynooghe. ECML 2005, 556-563. Web SearchBibTeXDownload
19Multi-agent Relational Reinforcement Learning. Tom Croonenborghs, Karl Tuyls, Jan Ramon, Maurice Bruynooghe. LAMAS 2005, 192-206. Web SearchBibTeXDownload
2004
18Searching for Compound Goals Using Relevancy Zones in the Game of Go. Jan Ramon, Tom Croonenborghs. Computers and Games 2004, 113-128. Web SearchBibTeXDownload
17Condensed Representations for Inductive Logic Programming. Luc De Raedt, Jan Ramon. KR 2004, 438-446. Web SearchBibTeXDownload
16Compact Representation of Knowledge Bases in Inductive Logic Programming. Jan Struyf, Jan Ramon, Maurice Bruynooghe, Sofie Verbaeten, Hendrik Blockeel. Machine Learning (57): 305-333 (2004). Web SearchBibTeXDownload
2003
15Relational Instance Based Regression for Relational Reinforcement Learning. Kurt Driessens, Jan Ramon. ICML 2003, 123-130. Web SearchBibTeXDownload
14Graph Kernels and Gaussian Processes for Relational Reinforcement Learning. Thomas Gärtner, Kurt Driessens, Jan Ramon. ILP 2003, 146-163. Web SearchBibTeXDownload
2002
13Clustering and instance based learning in first order logic. Jan Ramon. AI Commun. (15): 217-218 (2002). Web SearchBibTeXDownload
12Compact Representation of Knowledge Bases in ILP. Jan Struyf, Jan Ramon, Hendrik Blockeel. ILP 2002, 254-269. Web SearchBibTeXDownload
11Improving the Efficiency of Inductive Logic Programming Through the Use of Query Packs. Hendrik Blockeel, Luc Dehaspe, Bart Demoen, Guy Janssens, Jan Ramon, Henk Vandecasteele. J. Artif. Intell. Res. (JAIR) (16): 135-166 (2002). Web SearchBibTeXDownload
2001
10A polynomial time computable metric between point sets. Jan Ramon, Maurice Bruynooghe. Acta Inf. (37): 765-780 (2001). Web SearchBibTeXDownload
9Speeding Up Relational Reinforcement Learning through the Use of an Incremental First Order Decision Tree Learner. Kurt Driessens, Jan Ramon, Hendrik Blockeel. ECML 2001, 97-108. Web SearchBibTeXDownload
2000
8Learning a Go Heuristic with TILDE. Jan Ramon, Tom Francis, Hendrik Blockeel. Computers and Games 2000, 151-169. Web SearchBibTeXDownload
7Top-down induction of clustering trees. Hendrik Blockeel, Luc De Raedt, Jan Ramon. CoRR (cs.LG/0011032) (2000). Web SearchBibTeXDownload
6Executing Query Packs in ILP. Hendrik Blockeel, Luc Dehaspe, Bart Demoen, Gerda Janssens, Jan Ramon, Henk Vandecasteele. ILP 2000, 60-77. Web SearchBibTeXDownload
5Using Belief Networks to Neutralize Known Dependencies in Conceptual Clustering. Jan Ramon, Luc Dehaspe. ILP Work-in-progress reports 2000. Web SearchBibTeXDownload
1999
4Instance Based Function Learning. Jan Ramon, Luc De Raedt. ILP 1999, 268-278. Web SearchBibTeXDownload
3Generalizing Refinement Operators to Learn Prenex Conjunctive Normal Forms. Shan-Hwei Nienhuys-Cheng, Wim Van Laer, Jan Ramon, Luc De Raedt. ILP 1999, 245-256. Web SearchBibTeXDownload
1998
2Top-Down Induction of Clustering Trees. Hendrik Blockeel, Luc De Raedt, Jan Ramon. ICML 1998, 55-63. Web SearchBibTeX
1A Framework for Defining Distances Between First-Order Logic Objects. Jan Ramon, Maurice Bruynooghe. ILP 1998, 271-280. Web SearchBibTeXDownload
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