Universiteit Leiden

nl en

Hendrik Blockeel

Onderzoeker / gast

Naam
Dr.ir. H.L.W. Blockeel
Telefoon
+31 71 527 5778
E-mail
h.l.w.blockeel@liacs.leidenuniv.nl

Hendrik Blockeel (PhD in Computer Science, 1998, Katholieke Universiteit Leuven) is a professor ("hoogleraar") at the Katholieke Universiteit Leuven, and part-time associate professor ("universitair hoofddocent") at the University of Leiden, The Netherlands. His research interests include theory and algorithms for machine learning and data mining in general, with a particular focus on relational learning, graph mining, probabilistic logics, inductive knowledge bases, and applications of these techniques in the broader field of computer science, bio-informatics, and medical informatics.

Onderzoeker / gast

  • Wiskunde en Natuurwetenschappen
  • Leiden Inst Advanced Computer Sciences

Werkadres

Snellius
Niels Bohrweg 1
2333 CA Leiden
Kamernummer 123

Contact

  • Rahmani H., Blockeel H. & Bender A. (2016), Using a Human Drug Network for Generating Novel Hypotheses about Drugs, Intelligent Data Analysis 20(1): 183-197.artikel in tijdschrift (refereed)
  • Becerra-Bonache, Blockeel H.L.W. Galván M. & Jacquenet F. (2016), Learning Language Models from Images with ReGLL. In: Berendt B, Bringmann B, Fromont É., Garriga G., Miettinen P., Tatti N., Tresp V. (red.) Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2016. Lecture Notes in Computer Science, vol 9853. nr. 9853 Cham: Springer International Publishing. 55-58.congresbijdrage (refereed)
  • Verachtert A., Blockeel H.L.W. & Davis J. (2016), Dynamic Early Stopping for Naive Bayes. In: Kambhampati S. (red.) Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence. Palo Alto: AAAI Press / International Joint Conferences on Artificial Intelligence. 2082-2088.congresbijdrage (refereed)
  • Becerra-Bonache L., Blockeel H.L.W., Galván M. & Jacquenet F. (2016), Relational Grounded Language Learning. In: Kaminka G.A., Fox M., Bouquet P., Hüllermeier E., Dignum V., Dignum F., Harmelen F. van (red.) Proceedings of the 22nd European Conference on Artificial Intelligence pages. nr. 285: IOS Press. 1764-1765.congresbijdrage (refereed)
  • Dumancic S. & Blockeel H.L.W. (2016), An Efficient and Expressive Similarity Measure for Relational Clustering Using Neighbourhood Trees. In: Proceedings of the 22nd European Conference on Artificial Intelligence pages. nr. 285: IOS Press. 1674-1675.congresbijdrage (refereed)
  • Vanwinckelen G., Tragante do O V., Fierens D. & Blockeel H. (2016), Instance-level accuracy versus bag-level accuracy in multi-instance learning, Data Mining and Knowledge Discovery Journal 30(2): 313-341.artikel in tijdschrift (refereed)
  • Rahmani H., Blockeel H.L.W. & Bender A. (2015), Using a human disease network for augmenting prior knowledge about diseases, Intelligent Data Analysis 19(4): 897-916.artikel in tijdschrift (refereed)
  • Blockeel H.L.W. (2015), Data Mining: From Procedural to Declarative Approaches, New Generation Computing 33(2): 115-135.artikel in tijdschrift (refereed)
  • Bruynooghe M., Blockeel H.L.W., Bogaerts B., Cat B. de, Pooter S. De, Jansen J., Labarre A., Ramon J., Denecker M. & Verwer S. (2015), Predicate logic as a modeling language: modeling and solving some machine learning and data mining problems with IDP3, Theory and Practice of Logic Programming 15(6): 783-817.artikel in tijdschrift (refereed)
  • Becerra-Bonache L., Blockeel H.L.W., Galván M. & Jacquenet F. (2015), A First-Order-Logic Based Model for Grounded Language Learning. In: Proceedings Advances in Intelligent Data Analysis XIV - 14th International Symposium, IDA 2015. nr. LNCS 9385. 49-60.congresbijdrage (refereed)
  • Verbeeck D. & Blockeel H.L.W. (2015), Slower Can Be Faster: The iRetis Incremental Model Tree Learner. In: Proceedings Advances in Intelligent Data Analysis XIV - 14th International Symposium, IDA 2015. nr. LNCS 9385. 322-333.congresbijdrage (refereed)
  • Craenendonck T. van & Blockeel H.L.W. (2015), Limitations of using constraint set utility in semi-supervised clustering. In: Vanschoren, J., Brazdil P., Giraud-Carrier C., Kotthoff L. (red.) Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection (MetaSel 2015). nr. CEUR Workshop Proceedings 1455. Aachen, Germany: CEUR-WS. 27-42.congresbijdrage (refereed)
  • Adam A. & Blockeel H.L.W. (2015), Dealing with Overlapping Clustering: A Constraint-based Approach to Algorithm Selection. In: Proceedings of the 2015 International Workshop on Meta-Learning and Algorithm Selection (MetaSel 2015). nr. CEUR Workshop Proceedings 1455. 43-54.congresbijdrage (refereed)
  • Blockeel H.L.W., Leeuwen M. van & Vinciotti V. (Red.) (2014), Advances in Intelligent Data Analysis XIII - 13th International Symposium, IDA 2014 nr. LNCS 8819: Springer.boekredactie
  • Dumancic S., Adam A. & Blockeel H.L.W. (2014), Learning symbolic features for rule induction in computer aided diagnosis. In: Proceedings International Conference on Inductive Logic Programming.congresbijdrage (refereed)
  • Vanwinckelen G. & Blockeel H.L.W. (2014), A meta-learning system for multi-instance classification. In: Proceedings , International Workshop on Learning over Multiple Contexts.congresbijdrage (refereed)
  • Vanwinckelen G. & Blockeel H.L.W. (2014), Some insights into learner evaluation with cross-validation. In: Proceedings ECML/PKDD Workshop on Statistically Sound Data Mining.congresbijdrage (refereed)
  • Verbeeck, D. & Blockeel H.L.W. (2014), Sensitivity analysis of search-space dimensionality on recent multi-objective evolutionary algorithms. In: Proceedings 23rd Annual Belgian-Dutch Conference on Machine Learning (BENELEARN). 48-54.congresbijdrage (refereed)
  • Blockeel H, Kersting K, Nijssen S & Zelezný F (Red.) (2013), Proceedings Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part III Lecture Notes in Computer Science nr. 8190: Springer-Verlag.boekredactie
  • Blockeel H, Kersting K, Nijssen S & Zelezný F (Red.) (2013), Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part II Lecture Notes in Computer Science nr. 8189: Springer-Verlag.boekredactie
  • Blockeel H, Kersting K, Nijssen S & Zelezný F (Red.) (2013), Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part I Lecture Notes in Computer Science nr. 8188: Springer-Verlag.boekredactie
  • Shamsinejadbabaki P., Saraee M. & Blockeel H.L.W. (2013), Causality-based cost-effective action mining, Intelligent Data Analysis 17(6): 1075-1091.artikel in tijdschrift (refereed)
  • Taghipour N., Fierens D., Davis J. & Blockeel H.L.W. (2013), Lifted Variable Elimination: Decoupling the Operators from the Constraint Language, Journal of Artificial Intelligence Research 47: 393-439.artikel in tijdschrift (refereed)
  • Brijder R. & Blockeel H.L.W. (2013), On the inference of non-confluent NLC graph grammars, Journal of Logic and Computation 23(4): 799-814.artikel in tijdschrift (refereed)
  • Taghipour N., Fierens D., Broek G. Van den, Davis J. & Blockeel H.L.W. (2013), On the Completeness of Lifted Variable Elimination. In: Proceedings AAAI Workshop Statistical Relational Artificial Intelligence 2013.congresbijdrage (refereed)
  • Taghipour N., Fierens D., Broek G. Van den, Davis J. & Blockeel H.L.W. (2013), Completeness Results for Lifted Variable Elimination. In: Proceedings of the Sixteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2013. 572-580.congresbijdrage (refereed)
  • Hu P., Vens C., Verstrynge B. & Blockeel H.L.W. (2013), Generalizing from Example Clusters. In: Proceedings of Discovery Science 2013. 64-78.congresbijdrage (refereed)
  • Verbeeck D., Maes F., Grave K. De & Blockeel H.L.W. (2013), Multi-objective optimization with surrogate trees. In: Proceedings Genetic and Evolutionary Computation Conference, GECCO '13: ACM. 679-686.congresbijdrage (refereed)
  • Costa E.P., Verwer S. & Blockeel H.L.W. (2013), Estimating Prediction Certainty in Decision Trees. In: Proceedings Advances in Intelligent Data Analysis XII - 12th International Symposium, IDA 2013: Springer-Verlag. 138-149.congresbijdrage (refereed)
  • Taghipour N., Davis J. & Blockeel H.L.W. (2013), First-order Decomposition Trees. In: Proceedings Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. 1052-1060.congresbijdrage (refereed)
  • Adam A., Blockeel H.L.W., Govers S. & Aertsen A. (2013), SCCQL : A Constraint-Based Clustering System. In: Proceedings Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2013: Springer-Verlag. 681-684.congresbijdrage (refereed)
  • Blockeel H.L.W. (2013), Statistical Relational Learning. In: Handbook on Neural Information Processing 2013: Springer-Verlag. 241-281.boekdeel
  • Blockeel H.L.W., Kersting K., Nijssen S.G.R. & Zelezny F. (Red.) (2013), Data Mining Knowledge Discovery, Special Issue of the ECML PKDD 2013 journal track nr. 27(3).boekredactie
  • Blockeel H.L.W., Kersting K., Nijssen S.G.R. & Zelezny F. (Red.) (2013), Machine Learning, special issue of the ECML PKDD 2013 journal track nr. 93(1).boekredactie
  • Taghipour N., Fierens D., Davis J. & Blockeel H. (2012), Lifted Variable Elimination with Arbitrary Constraints, Journal of Machine Learning Research Pr. Tr. 22: 1194-1202.artikel in tijdschrift (refereed)
  • Meert W., Broeck G. van den, Taghipour N., Fierens D., Blockeel H., Davis J. & De Raedt L. (2012), Lifted inference for probabilistic programming. In: Proceedings of the NIPS Probabilistic Programming Workshop.congresbijdrage (refereed)
  • Taghipour N., Fierens D., Broeck G. van den, Davis J. & Blockeel H. (2012), Lifted variable Elimination: A Novel Operator and Completeness Results.congresbijdrage (refereed)
  • Piccart B., Blockeel H., Georges A. & Eeckhout L. (2012), Predictive learning in two-way datasets. Latest advances in inductive logic programming. In: International Conference on Inductive Logic Programming.congresbijdrage (refereed)
  • Blockeel H., Kersting K., Nijssen S. & Zelezny F. (2012), A Revised Publication Model for ECML PKDD. .: ArXiv.rapport
  • Andrews T., Blockeel H., Bogaerts H., Bruynooghe M., Denecker M., Pooter S. De, Mace C. & Ramon J. (2012), Analyzing manuscript traditions using constraint-based data mining. In: First Workshop on Combining Constraint Solving with Mining and Learning.congresbijdrage (refereed)
  • Blockeel H., Calders T., Fromont E., Goethals B., Prado A. & Robardet C. (2012), An inductive database system based on virtual mining views, Journal on Data Mining Knowledge Discovery 24(1): 247-287.artikel in tijdschrift (refereed)
  • Rahmani H., Blockeel H. & Bender A. (2012), Predicting Genes Involved in Human Cancer Using Network Contextual Information, Journal Integrative Bioinformatics 9(1).artikel in tijdschrift (refereed)
  • Blockeel H., Bogaerts B., Bruynooghe M., Cat B. de & Pooter S. De (2012), Modeling Machine Learning and Data Mining Problems with FO(.). In: Proceedings of the 28th International Conference on Logic Programming - Technical Communications (ICLP'12). 14-25.congresbijdrage (refereed)
  • Maervoet J., Vens C., Berghe G. Van den, Blockeel H. & Causmaecker P. De (2012), Outlier detection in relational data: A case study in geographical information systems, Expert Systems with Applications 39(5): 4718-4728.artikel in tijdschrift (refereed)
  • Driessens K., Vanwinckelen G. & Blockeel H. (2012), Meta-learning from an experiment database. In: ICML Workshop on Teaching Machine Learning.congresbijdrage (refereed)
  • Vanschoren J., Blockeel H., Pfahringer B. & Holmes G. (2012), Experiment databases, A new way to share, organize and learn from experiments, Machine Learning 87: 127-158.artikel in tijdschrift (refereed)
  • Vanwinckelen G. & Blockeel H. (2012), On estimating model accuracy with repeated cross-validation. In: BeneLearn 2012: Proceedings of the 21st Belgian-Dutch Conference on Machine Learningg (BeneLearn). 39-44.congresbijdrage (refereed)
  • Putten P.W.H. van der, Veenman C., Vanschoren J., Israel M. & Blockeel H. (Red.) (2011), Proceedings of the 20th Annual Belgian-Dutch Conference on Machine Learning (BENELEARN 2011). The Hague: Universiteit Leiden.boekredactie
  • Witsenburg M. & Blockeel H. (2011), K-means based approaches to clustering nodes in annotated graphs. In: Proceedings International Symposium on Methodologies for Intelligent Systems Lecture Notes in Computer Science: Springer.congresbijdrage (refereed)
  • Rahmani H., Blockeel H. & Bender A. (2011), Collaboration-Based Function Prediction in Protein-Protein Interaction Networks. In: Advances in Intelligent Data Analysis X - 10th Internationl Symposium Lecture notes in Computer Science: Springer. 318-327.congresbijdrage (refereed)
  • Kok J.N., Knobbe A., Blockeel H., Obladen B. & Koenders E. (2011), Large Data Stream Processing for Bridge Management Systems. In: Proceedings First Middle East Conference on Smart Monitoring, Assessment and Rehabilitation of Civil Structures (SMAR 2011).congresbijdrage (refereed)
  • Blockeel H. (2011), Hypothesis language. In: Sammut C., Webb G. (Red.) Encyclopedia of Machine Learning: Springer. 507-511.boekdeel
  • Tragante O. do, Fierens D. & Blockeel H. (2011), Instance-level accuracy versus bag-level accuracy in multi-instance learning. In: Proceedings 22nd Benelux Conference on Artificial Intelligence (BNAIC)..congresbijdrage (refereed)
  • Blockeel H., Borgwardt K., De Raedt L., Domingos P., Kersting K. & Yan X. (2011), Guest editorial to the special issue on inductive logic programming mining and learning in graphs and statistical relational learning, Machine Learning 83: 133-135.artikel in tijdschrift
  • Ray S., Scott S. & Blockeel H. (2011), Multi-instance learning. In: Sammut C., Webb G. (Red.) Encyclopedia of Machine Learning: Springer. 701-710.boekdeel
  • Blockeel H., Calders T., Fromont E., Goethals B., Prado A. & Robardet C. (2011), Inductive querying with virtual mining views. In: Dzeroski S., Goethals B., Panov P. (Red.) Inductive Databases and Queries: Constraint-Based Data Mining: Springer. 265-287.boekdeel
  • Uwents W., Monfardini G., Blockeel H., Gori M. & Scarselli F. (2011), Neural Networks for Relational Learning: An experimental comparison, Machine Learning 82(3): 315-349.artikel in tijdschrift (refereed)
  • Struyf J. & Blockeel H. (2011), Relational learning. In: Sammut C., Webb G. (Red.) Encyclopedia of Machine Learning: Springer. 851-857.boekdeel
  • Paula Costa E. De, Vens C. & Blockeel H. (2011), Protein Subfamily Identification using Clustering Trees, Proceedings 20th Belgian Dutch Conference on Machine Learning (BENELEARN) : 105-106.abstract
  • Blockeel H. (2011), Bias Specification Language. In: Encyclopedia of Machine Learning 1. 90-100.boekdeel
  • Brijder R. & Blockeel H. (2011), Characterizing compressibility of disjoint subgraphs with NLC grammars. In: Proceedings Fifth International conference on Language and Automata Theory and Applications (LATA 2011) Lecture notes in Computer Science. 167-178.congresbijdrage (refereed)
  • Blockeel H. (2011), Hypothesis Space. In: Encyclopedia of Machine Learning 1. 511-513.boekdeel
  • Blockeel H., Calders T., Fromont E., Goethals B., Prado A. & Robardet C. (2011), A practical comparative study of data mining query languages. In: Dzeroski S., Goethals B., Panov P. (Red.) Inductive Databases and Constraint-Based Data Mining: Springer. 59-77.boekdeel
  • Paula Costa E. De, Vens C. & Blockeel H. (2011), Identification and Classification of Protein Subfamilies using To-Down Phylogenetic Tree Reconstruction, Proceedings European Conference on Computational Biology .abstract
  • Rahmani H., Blockeel H. & Bender A. (2011), Interaction-based feature selection for predicting cancer-related proteins in protein-protein interaction networks Proceedings Fifth International Workshop on Machine Learning in System Biology.congresbijdrage (refereed)
  • Blockeel H. (2011), Statistical relational learning. In: Bianchini M., Maggini M., Jain L. (Red.) Handbook of Neural Information Processing.boekdeel
  • Blockeel H. (2011), Observation Language. In: Encyclopedia of Machine Learning 1. 733-735.boekdeel
  • Piccart B., Georges A., Blockeel H. & Eeckhout L. (2011), Ranking Commercial Machines Through Data Transposition. In: Proceedings IEEE International Symposium on Workload Characterization (IISWC). 3-14.congresbijdrage (refereed)
  • Witsenburg M. & Blockeel H. (2011), Improving the accuracy of similarity measures by using link information. In: Proceedings International Symposium on Methodologies for Intelligent Systems Lecture notes in Computer Science: Springer.congresbijdrage (refereed)
  • Rahmani H., Blockeel H. & Bender A. (2010), Collaboration based function prediction in protein-protein interaction networks, Proceedings of the 7th International Symposium on Networks in Bioinformatics .abstract
  • Fierens D., Ramon J., Blockeel H. & Bruynooghe M. (2010), A comparison of pruning criteria for probability trees, Machine Learning 78: 251-285.artikel in tijdschrift (refereed)
  • Wiele T. Van de, Tragante Do O.V., Silva R. Alves da & Blockeel H. (2010), Knowledge discovery in panoramic X-rays for postmortem identification. In: Proceedings of BNAIC. Benelux Conference on Artificial Intelligence. 1-6.congresbijdrage (refereed)
  • Rahmani H., Nobakht B. & Blockeel H. (2010), Collaboration-based social tag prediction in the graph of annotated web pages DyNaK 2010: Dynamic Networks and Knowledge Discovery, Proceedings of the 9th European Conference on Computational Biology : 1-12.abstract
  • Meert W., Taghipour N. & Blockeel H. (2010), First-order Bayes-ball. In: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2010) Lecture Notes in Computer Science: Springer.congresbijdrage (refereed)
  • Knobbe A., Blockeel H., Koopman A., Calders T., Obladen Bas, Bosma C., Galenkamp H., Koenders E. & Kok J.N. (2010), InfraWatch: Data management of large systems for monitoring infrastructural performance. In: Intelligent Data Analysis (IDA) Lecture notes in Computer Science: Springer. 91-102.congresbijdrage (refereed)
  • Rahmani H., Blockeel H. & Bender A. (2010), Collaboration-based function prediction in protein-protein interaction networks. In: Machine Learning in Systems Biology: Proceedings of the Fourth International Workshop. 55-58.congresbijdrage (refereed)
  • Paula Costa E. De, Vens C. & Blockeel H. (2010), Reconstructing phylogenetic trees from clustering trees, Proceedings European Conference on Computational Biology .abstract
  • Blockeel H., Piccart B., Rahmani H. & Fierens D. (2010), Three complementary approaches to context aware movie recommendation. In: Proceedings of the Workshop on Context-Aware Movie Recommendation: ACM. 57-60.congresbijdrage (refereed)
  • Uwents W., Monfardini G., Blockeel H., Gori M. & Scarselli F. (2010), Neural networks for relational learning: An experimental comparison, Machine Learning.artikel in tijdschrift (refereed)
  • Rahmani H., Blockeel H. & Bender A. (2010), Predicting the functions of proteins in protein-protein interaction networks from global information. In: JMLR: Workshop and Conference Proceedings: International Workshop on Machine Learning in Systems Biology. 82-97.congresbijdrage (refereed)
  • Vens C., De Paula Costa E. & Blockeel H. (2010), Top-down induction of phylogenetic trees. In: European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics Lecture Notes in Computer Science: Springer. 62-73.congresbijdrage (refereed)
  • Loon K. Van, Guiza Grandas F., Meyfroidt G., Aerts J., Ramon J., Blockeel H., Bruynooghe M., Berghe G. Van den & Berckmans D. (2010), Prediction of Clinical Conditions after Coronary Bypass Surgery using Dynamic Data Analysis, Journal of Medical Systems 34(3): 229-239.artikel in tijdschrift (refereed)
  • Blockeel H. & Witsenburg M. (2010), Exploiting homophily in unsupervised learning, Lorentz Workshop on Mining Patterns and Subgroups .abstract
  • Rahmani H., Blockeel H. & Bender A. (2010), Collaboration-based function prediction in protein-protein interaction networks, Proceedings European Conference on Computational Biology .abstract
  • Blockeel H., Rahmani H. & Witsenburg M. (2010), On the importance of similarity measures for planning to learn. In: Brazdil P., Bernstein A., Kietz J. (Red.) 19th European Conference on Artificial Intelligence, 3rd Planning to Learn workshop (PlanLearn-2010). 69-74.congresbijdrage (refereed)
  • Ray S., Scott S. & Blockeel H. (2010), Multi-instance learning. In: C. Sammut G. Webb (Red.) Encyclopedia of Machine Learning: Springer.boekdeel
  • Vanschoren J. & Blockeel H. (2010), Experiment databases Inductive Databases and Queries: Constraint-based Data Mining. In: Dzeroski S., Goethals B., Panov P. (Red.) Inductive Databases and Queries: Constraint-based Data Mining: Springer.boekdeel
  • Meert W., Struyf J. & Blockeel H. (2010), Contextual variable elimination with overlapping contexts. In: Proceedings of the Fifth European Workshop on Probabilistic Graphical Models (PGM2010). 193-201.congresbijdrage (refereed)
  • Schietgat L., Vens C., Struyf J., Blockeel H., Kocev D. & Dzeroski S. (2010), Predicting gene function using hierarchical multi-label decision tree ensembles, BMC bioinformatics 11: 2.artikel in tijdschrift (refereed)
  • Taghipour N., Fierens D. & Blockeel H. (2010), Probabilistic logical learning for biclustering: A case study with surprising results: K.U. Leuven.rapport
  • Vens C., Schietgat L., Struyf J., Blockeel H., Kocev D. & Dzeroski S. (2010), Predicting gene functions using predictive clustering trees Inductive Databases and Queries: Constraint-based Data Mining. In: Dzeroski S., Goethals B., Panov P. (Red.) Inductive Databases and Queries: Constraint-based Data Mining: Springer.boekdeel
  • Vanschoren J. & Blockeel H. (2009), Stand on the shoulders of giants. Towards a portal for collaborative experimentation in data mining. In: Proceedings of the SoKD-09 International Workshop on Third Generation Data Mining at ECML PKDD 2009. 88-99.congresbijdrage (refereed)
  • Verschoren J. & Blockeel H. (2009), A community-based platform for machine learning experimentation. In: Machine Learning and Knowledge Discovery in Databases, European Conference ECML PKDD 2009 Lecture notes in Computer Science: Springer. 750-754.congresbijdrage (refereed)
  • Meert W., Struyf J. & Blockeel H. (2009), CP-logic theory inference with contextual variable elimination and comparison to BDD based inference methods. In: Proceedings of the 19th International Conference on Inductive Logic Programming (ILP).congresbijdrage (refereed)
  • Blockeel H. & Brijder R. (2009), Learning non-confluent NLC graph grammar rules. In: Mathematical Theory and Computational Practice, Fifth Conference on Computability in Europe, CiE 2009: University of Heidelberg. 60-69.congresbijdrage (refereed)
  • Rahmani H., Blockeel H. & Bender A. (2009), Predicting the functions of proteins in PPI networks from global information. In: Proceedings of the Third International Workshop on Machine Learning in Systems Biology: Helsinki University Printing House. 85-94.congresbijdrage (refereed)
  • Loon K. Van, Guiza Grandas F., Meyfroidt G., Aerts J.-M., Ramon J., Blockeel H., Bruynooghe M., Van den Berghe G. & Berckmans D. (2009), Dynamic Data Analysis and Data Mining for Prediction of Clinical Stability. In: Medical Informatics Europe, edition 22. 590-594.congresbijdrage (refereed)
  • Paula Costa E. De, Vens C. & Blockeel H. (2009), Top-down phylogenetic tree reconstruction: a decision tree approach. In: International Workshop on Machine Learning in Systems Biology.congresbijdrage (refereed)
  • Schietgat L., Theys K., Ramon J., Blockeel H. & Vandamme A. (2008), Distinguishing epidemiological dependent from treatment (resistance) dependent HIV mutations: problem statement. In: Proceedings of the 1st International Workshop on Statistical and Relational Learning in Bioinformatics.congresbijdrage (refereed)
  • Vanschoren J., Blockeel H., Pfahringer B. & Holmes G. (2008), Experiment databases: Creating a new platform for meta-learning research. In: Proceedings of the ICML/COLT/UAI. 10-15.congresbijdrage (refereed)
  • Witsenburg M. & Blockeel H. (2008), A method to extend existing document clustering procedures in order to include relational information. In: Kaski, S., Vishwanathan, V., Wrobel, S. (Red.) 6th International Workshop on Mining and Learning With Graphs. 1-3.congresbijdrage (refereed)
  • Drouillon P. & Blockeel H. (2008), Prediction of molecular substructures from mass spectrograms using constraint based clustering. In: Kaski, S., Vishwanathan, S., Wrobel, S. (Red.) 6th International Workshop on Mining and Learning With Graphs. 1-4.congresbijdrage (refereed)
  • Blockeel H. & Nijssen S. (2008), Induction of node label controlled graph grammar rules. In: Kaski, S., Vishwanathan, S., Wrobel, S. (Red.) 6th International Workshop on Mining and Learning with Graphs. 1-4.congresbijdrage (refereed)
  • Blockeel H., Calders T., Fromont E., Goethals B. & Prado A. (2008), Mining Views: Database Views for Data Mining. In: IEEE 24th International Conference on Data Engineering. 1608-1611.congresbijdrage (refereed)
  • Meert W., Struyf J. & Blockeel H. (2008), Learning Ground CP-Logic Theories by Leveraging Bayesian Network Learning Techniques, Fundam. Inform. 89(1): 131-160.artikel in tijdschrift (refereed)
  • Blockeel H., Calders T., Fromont E., Goethals B., Prado A. & Robardet C. (2008), An Inductive Database Prototype Based on Virtual Mining Views. In: 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 1061-1064.congresbijdrage (refereed)
  • Schietgat L., Ramon J., Bruyooghe M. & Blockeel H. (2008), An Efficiently Computable Graph-Based Metric for the Classification of Small Molecules. In: Discovery Science. Berlin / Heidelberg: Springer. 197-209.boekdeel
  • Vanschoren J. & Blockeel H. (2008), Investigating classifier learning behavior with experiment databases. In: Preisach, C., Burkhardt, H., Schmidt-Thieme, L., Decker, R. (Red.) Data Analysis, Machine Learning and Applications. Berlin Heidelberg: Springer. 421-428.boekdeel
  • Uwents W. & Blockeel H. (2008), Learning Aggregate Functions with Neural Networks Using a Cascade-Correlation Approach. In: Inductive Logic Programming. Berlin / Heidelberg: Springer. 315-329.boekdeel
  • Piccart B., Struyf J. & Blockeel H. (2008), Empirical Asymmetric Selective Transfer in Multi-objective Decision Trees. In: Discovery Science. Berlin / Heidelberg: Springer. 64-75.boekdeel
  • Meert W., Struyf J. & Blockeel H. (2008), Learning ground CP-logic theories by leveraging Bayesian network learning technique, Fundamenta informaticae.artikel in tijdschrift (refereed)
  • Blockeel H. (2008), Exposing the Causal Structure of Processes by Learning CP-Logic Programs. In: PRICAI 2008. 2.congresbijdrage (refereed)
  • Vanschoren J., Blockeel H., Pfahringer B. & Holmes G. (2008), Organizing the World's Machine Learning Information. In: . ISoLA 2008. 693-708.congresbijdrage (refereed)
  • Uwents W. & Blockeel H. (2008), A Comparison between Neural Network Methods for Learning Aggregate Functions. In: Discovery Science. Berlin / Heidelberg: Springer. 88-99.boekdeel
  • Vens C., Struyf J., Schietgat L., Dzeroski S. & Blockeel H. (2008), Decision trees for hierarchical multi-label classification, Machine Learning 73(2): 185-214.artikel in tijdschrift (refereed)
  • Vanschoren J., Blockeel H., Pfahringer B. & Holmes G. (2008), Organizing the World’s Machine Learning Information. In: Leveraging Applications of Formal Methods, Verification and Validation. Berlin / Heidelberg: Springer. 693-708.boekdeel
  • Blockeel H., Shavlik J.W. & Tadepalli P. (2008), Guest editors' introduction: special issue on inductive logic programming, Machine Learning 73(1): 1-2.artikel in tijdschrift (refereed)
  • Blockeel H., Shavlik J.W. & Tadepalli P. (2008), Guest editors’ introduction: Special issue on inductive logic programming, Machine Learning 73(1): 1-2.artikel in tijdschrift (refereed)
  • Ramon J., Croonenborghs T., Fierens D., Blockeel H. & Bruynooghe M. (2008), Generalized ordering-search for learning directed probabilistic logical models, Machine Learning 70(2-3): 169-188.artikel in tijdschrift (refereed)
  • Fromont E., Blockeel H. & Struyf J. (2007), Integrating decision tree learning into inductive databases, Knowledge Discovery in Inductive Databases. In: Dzeroski, S., Struyf, J. (Red.) 5th International Workshop, KDID 2006, Berlin, Germany, September 18, 2006, Revised Selected and Invited Papers Lecture notes in Computer Science. 81-96.congresbijdrage (refereed)
  • Vanschoren J. & Blockeel H. (2007), Investigating classifier learning behavior with experiment databases. In: Proceedings of The 31st Annual Conference of the German Classification Society on Data Analysis, Machine Learning, and Applications. Freiburg.congresbijdrage (refereed)
  • Ramon J., Croonenborghs T., Fierens D., Blockeel H. & Bruynooghe M. (2007), Generalized ordering-search for learning directed probabilistic logical models. In: Muggleton, S., Otero, R., Tamaddoni-Nezhad, A. (Red.) Inductive Logic Programming, ILP 2006, Revised Selected Papers Lecture notes in Computer Science. 40-42.congresbijdrage (refereed)
  • Assche A. van & Blockeel H. (2007), Seeing the Forest Through the Trees: Learning a Comprehensible Model from an Ensemble. In: Kok, J., Koronacki, J., López de Mántaras, R., Matwin, S., Mladenic, D., Skowron, A. (Red.) Machine Learning: ECML Lecture notes in Computer Science: Springer. 418-429.congresbijdrage (refereed)
  • Blockeel H., Witsenburg M. & Kok J.N. (2007), Hypergraphs, and Inductive Logic Programming. In: Paolo Frasconi, Kristian Kersting, Koji Tsuda (Red.) Mining and Learning with Graphs. 93-96.congresbijdrage (refereed)
  • Vens C., Ramon J. & Blockeel H. (2007), ReMauve, a relational model tree learner. In: Muggleton, S., Otero, R., Tamaddoni-Nezhad, A (Red.) Inductive Logic Programming Lecture notes in Computer Science. 424-438.congresbijdrage (refereed)
  • Ramon J., Fierens D., Güiza F., Meyfroidt G. & Blockeel H. (2007), Mining data from intensive care patients, Advanced Engineering Informatics 21(3): 243-256.artikel in tijdschrift (refereed)
  • Fierens D., Ramon J., Bruynooghe M. & Blockeel H. (2007), Learning Directed Probabilistic Logical Models: Ordering-Search Versus Structure-Search. In: Kok, J.N., Koronacki, J., López de Mántaras, R., Matwin, S., Mladenic, D., Skowron, A. (Red.) Machine Learning: ECML 2007, 18th European Conference on Machine Learning Lecture notes in Computer Science: Springer. 567-574.congresbijdrage (refereed)
  • Blockeel H., Ramon J., Shavlik J.W. & Tadepalli P. (2007), Inductive Logic Programming. Berlin: Springer.boek
  • Vanschoren J., Assche A. van, Vens C. & Blockeel H. (2007), Meta-learning from experiment databases: An illustration. In: Someren, M. van, Katrenko, S., Adriaans, P. (Red.) Machine Learning Conference of Belgium and The Netherlands. 120-127.congresbijdrage (refereed)
  • Croonenborghs T., Ramon J., Blockeel H. & Bruynooghe M. (2007), Online Learning and Exploiting Relational Models in Reinforcement Learning. In: IJCAI 2007, Proceedings of the 20th International Joint Conference on Artificial Intelligence. 726-731.congresbijdrage (refereed)
  • Meert W., Struyf J. & Blockeel H. (2007), Learning ground CP-logic theories by means by Bayesian network techniques. In: Malerba, D., Appice, A., Ceci, M. (Red.) Proceedings of the 6th International Workshop on Multi-Relational Data Mining. 93-104.congresbijdrage (refereed)
  • Hoste K., Eeckhout L. & Blockeel H. (2007), Analyzing commercial processor performance numbers for predicting performance of applications of interest. In: Golubchik, L., Ammar, M.H., Harchol-Balter, M. (Red.) Proceedings of the 2007 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems. San Diego: ACM. 375-376.congresbijdrage (refereed)
  • Blockeel H. & Meert W. (2007), Towards learning non-recursive LPADs by transforming them into Bayesian networks. In: Muggleton, S., Otero, R., Tamaddoni-Nezhad, A. (Red.) Inductive Logic Programming, ILP 2006, Revised Selected Papers Lecture notes in Computer Science. 94-108.congresbijdrage (refereed)
  • Blockeel H. & Vanschoren J. (2007), Experiment databases: Towards an improved experimental methodology in machine learning. In: Kok, J.N., Koronacki, J., Lopez de Mantaras, R., Matwin, S., Mladenic, D., Skowron, A. (Red.) Knowledge Discovery in Databases: PKDD 2007, 11th European Conference on Principles and Practice of Knowledge Discovery in Databases Lecture notes in Computer Science. 6-17.congresbijdrage (refereed)
  • Ramon J., Dubrovskaya S. & Blockeel H. (2007), Learning resistance mutation pathways of HIV. In: Proceedings of The Sixteenth Annual Machine Learning Conference of Belgium and the Netherlands.congresbijdrage (refereed)
  • Blockeel H., Calders T., Fromont E., Goethals B. & Prado A. (2007), Mining views: Database views for data mining. In: Nijssen, S. and De Raedt, L. (Red.) Proceedings of the 1st International Workshop on Constraint-Based Mining and Learning. 21-33.congresbijdrage (refereed)
  • Vens C. & Blockeel H. (2007), Using clustering trees for learning phylogenetic trees. In: Frasconi, P., Kersting, K., Tsuda, K., (Red.) Proceedings of the 5th International Workshop on Mining and Learning with Graphs. 143-146.congresbijdrage (refereed)
  • Drouillon P. & Blockeel H. (2007), Prediction of molecular substructures from mass spectograms. In: Frasconi, P., Kersting, K., Tsuda, K. (Red.) Prediction of molecular substructures from mass spectograms. 171-174.congresbijdrage (refereed)
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