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Jan Ramon: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Daan Fierens, Hendrik Blockeel, Maurice Bruynooghe, Jan Ramon
    Logical Bayesian Networks and Their Relation to Other Probabilistic Logical Models. [Citation Graph (0, 0)][DBLP]
    BNAIC, 2005, pp:343-344 [Conf]
  2. Jan Ramon, Tom Croonenborghs
    Searching for Compound Goals Using Relevancy Zones in the Game of Go. [Citation Graph (0, 0)][DBLP]
    Computers and Games, 2004, pp:113-128 [Conf]
  3. Jan Ramon, Tom Francis, Hendrik Blockeel
    Learning a Go Heuristic with TILDE. [Citation Graph (0, 0)][DBLP]
    Computers and Games, 2000, pp:151-169 [Conf]
  4. Kurt Driessens, Jan Ramon, Hendrik Blockeel
    Speeding Up Relational Reinforcement Learning through the Use of an Incremental First Order Decision Tree Learner. [Citation Graph (0, 0)][DBLP]
    ECML, 2001, pp:97-108 [Conf]
  5. Daan Fierens, Jan Ramon, Hendrik Blockeel, Maurice Bruynooghe
    A Comparison of Approaches for Learning Probability Trees. [Citation Graph (0, 0)][DBLP]
    ECML, 2005, pp:556-563 [Conf]
  6. Hendrik Blockeel, Luc De Raedt, Jan Ramon
    Top-Down Induction of Clustering Trees. [Citation Graph (0, 0)][DBLP]
    ICML, 1998, pp:55-63 [Conf]
  7. Kurt Driessens, Jan Ramon
    Relational Instance Based Regression for Relational Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    ICML, 2003, pp:123-130 [Conf]
  8. Tom Croonenborghs, Jan Ramon, Hendrik Blockeel, Maurice Bruynooghe
    Online Learning and Exploiting Relational Models in Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2007, pp:726-731 [Conf]
  9. Daan Fierens, Hendrik Blockeel, Maurice Bruynooghe, Jan Ramon
    Logical Bayesian Networks and Their Relation to Other Probabilistic Logical Models. [Citation Graph (0, 0)][DBLP]
    ILP, 2005, pp:121-135 [Conf]
  10. Thomas Gärtner, Kurt Driessens, Jan Ramon
    Graph Kernels and Gaussian Processes for Relational Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    ILP, 2003, pp:146-163 [Conf]
  11. Hendrik Blockeel, Luc Dehaspe, Bart Demoen, Gerda Janssens, Jan Ramon, Henk Vandecasteele
    Executing Query Packs in ILP. [Citation Graph (0, 0)][DBLP]
    ILP, 2000, pp:60-77 [Conf]
  12. Jan Struyf, Jan Ramon, Hendrik Blockeel
    Compact Representation of Knowledge Bases in ILP. [Citation Graph (0, 0)][DBLP]
    ILP, 2002, pp:254-269 [Conf]
  13. Shan-Hwei Nienhuys-Cheng, Wim Van Laer, Jan Ramon, Luc De Raedt
    Generalizing Refinement Operators to Learn Prenex Conjunctive Normal Forms. [Citation Graph (0, 0)][DBLP]
    ILP, 1999, pp:245-256 [Conf]
  14. Jan Ramon, Maurice Bruynooghe
    A Framework for Defining Distances Between First-Order Logic Objects. [Citation Graph (0, 0)][DBLP]
    ILP, 1998, pp:271-280 [Conf]
  15. Jan Ramon, Luc Dehaspe
    Using Belief Networks to Neutralize Known Dependencies in Conceptual Clustering. [Citation Graph (0, 0)][DBLP]
    ILP Work-in-progress reports, 2000, pp:- [Conf]
  16. Jan Ramon, Luc De Raedt
    Instance Based Function Learning. [Citation Graph (0, 0)][DBLP]
    ILP, 1999, pp:268-278 [Conf]
  17. Tamás Horváth, Jan Ramon, Stefan Wrobel
    Frequent subgraph mining in outerplanar graphs. [Citation Graph (0, 0)][DBLP]
    KDD, 2006, pp:197-206 [Conf]
  18. Luc De Raedt, Jan Ramon
    Condensed Representations for Inductive Logic Programming. [Citation Graph (0, 0)][DBLP]
    KR, 2004, pp:438-446 [Conf]
  19. Tom Croonenborghs, Karl Tuyls, Jan Ramon, Maurice Bruynooghe
    Multi-agent Relational Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    LAMAS, 2005, pp:192-206 [Conf]
  20. Tamás Horváth, Jan Ramon, Stefan Wrobel
    Frequent Subgraph Mining in Outerplanar Graphs. [Citation Graph (0, 0)][DBLP]
    LWA, 2006, pp:290-296 [Conf]
  21. Celine Vens, Jan Ramon, Hendrik Blockeel
    Refining Aggregate Conditions in Relational Learning. [Citation Graph (0, 0)][DBLP]
    PKDD, 2006, pp:383-394 [Conf]
  22. Jan Ramon, Maurice Bruynooghe
    A polynomial time computable metric between point sets. [Citation Graph (0, 0)][DBLP]
    Acta Inf., 2001, v:37, n:10, pp:765-780 [Journal]
  23. Jan Ramon
    Clustering and instance based learning in first order logic. [Citation Graph (0, 0)][DBLP]
    AI Commun., 2002, v:15, n:4, pp:217-218 [Journal]
  24. Hendrik Blockeel, Luc De Raedt, Jan Ramon
    Top-down induction of clustering trees [Citation Graph (0, 0)][DBLP]
    CoRR, 2000, v:0, n:, pp:- [Journal]
  25. 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. [Citation Graph (0, 0)][DBLP]
    J. Artif. Intell. Res. (JAIR), 2002, v:16, n:, pp:135-166 [Journal]
  26. Jan Struyf, Jan Ramon, Maurice Bruynooghe, Sofie Verbaeten, Hendrik Blockeel
    Compact Representation of Knowledge Bases in Inductive Logic Programming. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2004, v:57, n:3, pp:305-333 [Journal]
  27. Kurt Driessens, Jan Ramon, Thomas Gärtner
    Graph kernels and Gaussian processes for relational reinforcement learning. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2006, v:64, n:1-3, pp:91-119 [Journal]
  28. Robby Goetschalckx, Jan Ramon
    On Policy Learning in Restricted Policy Spaces. [Citation Graph (0, 0)][DBLP]
    AAAI, 2007, pp:1858-1859 [Conf]
  29. Daan Fierens, Jan Ramon, Maurice Bruynooghe, Hendrik Blockeel
    Learning Directed Probabilistic Logical Models: Ordering-Search Versus Structure-Search. [Citation Graph (0, 0)][DBLP]
    ECML, 2007, pp:567-574 [Conf]
  30. Jan Ramon, Kurt Driessens, Tom Croonenborghs
    Transfer Learning in Reinforcement Learning Problems Through Partial Policy Recycling. [Citation Graph (0, 0)][DBLP]
    ECML, 2007, pp:699-707 [Conf]
  31. Jan Ramon, Tom Croonenborghs, Daan Fierens, Hendrik Blockeel, Maurice Bruynooghe
    Generalized Ordering-Search for Learning Directed Probabilistic Logical Models. [Citation Graph (0, 0)][DBLP]
    ILP, 2006, pp:40-42 [Conf]
  32. Celine Vens, Jan Ramon, Hendrik Blockeel
    ReMauve: A Relational Model Tree Learner. [Citation Graph (0, 0)][DBLP]
    ILP, 2006, pp:424-438 [Conf]
  33. Jan Ramon, Daan Fierens, Fabián Güiza, Geert Meyfroidt, Hendrik Blockeel, Maurice Bruynooghe, Greet Vanden Berghe
    Mining data from intensive care patients. [Citation Graph (0, 0)][DBLP]
    Advanced Engineering Informatics, 2007, v:21, n:3, pp:243-256 [Journal]

  34. Bayes-Relational Learning of Opponent Models from Incomplete Information in No-Limit Poker. [Citation Graph (, )][DBLP]


  35. Learning with whom to communicate using relational reinforcement learning. [Citation Graph (, )][DBLP]


  36. An Efficiently Computable Graph-Based Metric for the Classification of Small Molecules. [Citation Graph (, )][DBLP]


  37. Active Learning for High Throughput Screening. [Citation Graph (, )][DBLP]


  38. Using Decision Trees as the Answer Networks in Temporal Difference-Networks. [Citation Graph (, )][DBLP]


  39. Anti-monotonic Overlap-Graph Support Measures. [Citation Graph (, )][DBLP]


  40. Learning Directed Probabilistic Logical Models Using Ordering-Search. [Citation Graph (, )][DBLP]


  41. Handling missing values and censored data in PCA of pharmacological matrices. [Citation Graph (, )][DBLP]


  42. Efficient Frequent Connected Subgraph Mining in Graphs of Bounded Treewidth. [Citation Graph (, )][DBLP]


  43. General Graph Refinement with Polynomial Delay. [Citation Graph (, )][DBLP]


  44. A Polynomial-time Metric for Outerplanar Graphs. [Citation Graph (, )][DBLP]


  45. Monte-Carlo Tree Search in Poker Using Expected Reward Distributions. [Citation Graph (, )][DBLP]


  46. Dynamic Data Analysis and Data Mining for Prediction of Clinical Stability. [Citation Graph (, )][DBLP]


  47. Learning directed probabilistic logical models: ordering-search versus structure-search. [Citation Graph (, )][DBLP]


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