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ORCIDHendrik Blockeel
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- affiliation: Catholic University of Leuven, Belgium
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2020 – today
- 2024
[j51]Daan Van Wesenbeeck
, Aras Yurtman, Wannes Meert, Hendrik Blockeel:
LoCoMotif: discovering time-warped motifs in time series. Data Min. Knowl. Discov. 38(4): 2276-2305 (2024)- [c120]Kshitij Goyal, Sebastijan Dumancic, Hendrik Blockeel:
DeepSaDe: Learning Neural Networks That Guarantee Domain Constraint Satisfaction. AAAI 2024: 12199-12207 - 2023
- [j50]Hendrik Blockeel, Laurens Devos, Benoît Frénay, Géraldin Nanfack, Siegfried Nijssen:
Decision trees: from efficient prediction to responsible AI. Frontiers Artif. Intell. 6 (2023) - [j49]Lola Botman, Jonas Soenen, Konstantinos Theodorakos, Aras Yurtman, Jessa Bekker, Koen Vanthournout, Hendrik Blockeel, Bart De Moor, Jesus Lago:
A Scalable Ensemble Approach to Forecast the Electricity Consumption of Households. IEEE Trans. Smart Grid 14(1): 757-768 (2023) - [c119]Aras Yurtman, Jonas Soenen, Wannes Meert, Hendrik Blockeel:
Estimating Dynamic Time Warping Distance Between Time Series with Missing Data. ECML/PKDD (5) 2023: 221-237 - [c118]Youmna Ismaeil, Daria Stepanova, Trung-Kien Tran, Hendrik Blockeel:
FeaBI: A Feature Selection-Based Framework for Interpreting KG Embeddings. ISWC 2023: 599-617 - [c117]Huu Tan Mai, Youmna Ismaeil, Daria Stepanova, Trung-Kien Tran, Hendrik Blockeel:
Look beyond the Surface: A Demo for Explaining Knowledge Graph Embeddings and Entity Similarity. ISWC (Posters/Demos/Industry) 2023 - [i28]Kshitij Goyal, Sebastijan Dumancic, Hendrik Blockeel:
DeepSaDe: Learning Neural Networks that Guarantee Domain Constraint Satisfaction. CoRR abs/2303.01141 (2023) - [i27]Jonas Soenen, Elia Van Wolputte, Vincent Vercruyssen, Wannes Meert, Hendrik Blockeel:
AD-MERCS: Modeling Normality and Abnormality in Unsupervised Anomaly Detection. CoRR abs/2305.12958 (2023) - [i26]Daan Van Wesenbeeck, Aras Yurtman, Wannes Meert, Hendrik Blockeel:
LoCoMotif: Discovering time-warped motifs in time series. CoRR abs/2311.17582 (2023) - 2022
- [c116]Jonas Schouterden, Jessa Bekker, Jesse Davis, Hendrik Blockeel:
Unifying Knowledge Base Completion with PU Learning to Mitigate the Observation Bias. AAAI 2022: 4137-4145 - [c115]Kshitij Goyal, Wannes Meert, Hendrik Blockeel, Elia Van Wolputte, Koen Vanderstraeten, Wouter Pijpops, Kurt Jaspers:
Automatic Generation of Product Concepts from Positive Examples, with an Application to Music Streaming. BNAIC/BENELEARN 2022: 47-64 - [c114]Kshitij Goyal, Sebastijan Dumancic, Hendrik Blockeel:
SaDe: Learning Models that Provably Satisfy Domain Constraints. ECML/PKDD (5) 2022: 410-425 - [c113]Youmna Ismaeil, Daria Stepanova, Trung-Kien Tran, Piyapat Saranrittichai, Csaba Domokos, Hendrik Blockeel:
Towards Neural Network Interpretability Using Commonsense Knowledge Graphs. ISWC 2022: 74-90 - [i25]Florian Busch, Moritz Kulessa, Eneldo Loza Mencía, Hendrik Blockeel:
Combining Predictions under Uncertainty: The Case of Random Decision Trees. CoRR abs/2208.07403 (2022) - [i24]Kshitij Goyal, Wannes Meert, Hendrik Blockeel, Elia Van Wolputte, Koen Vanderstraeten, Wouter Pijpops, Kurt Jaspers:
Automatic Generation of Product Concepts from Positive Examples, with an Application to Music Streaming. CoRR abs/2210.01515 (2022) - 2021
- [c112]Florian Busch, Moritz Kulessa, Eneldo Loza Mencía, Hendrik Blockeel:
Combining Predictions Under Uncertainty: The Case of Random Decision Trees. DS 2021: 78-93 - [i23]Kshitij Goyal, Sebastijan Dumancic, Hendrik Blockeel:
SaDe: Learning Models that Provably Satisfy Domain Constraints. CoRR abs/2112.00552 (2021) - 2020
- [c111]Elia Van Wolputte, Hendrik Blockeel:
Missing Value Imputation with MERCS: A Faster Alternative to MissForest. DS 2020: 502-516 - [c110]Jonas Schouterden, Jesse Davis, Hendrik Blockeel:
Multi-directional Rule Set Learning. DS 2020: 517-532 - [c109]Jonas Soenen, Sebastijan Dumancic, Toon van Craenendonck, Hendrik Blockeel:
Tackling Noise in Active Semi-supervised Clustering. ECML/PKDD (2) 2020: 121-136 - [c108]Evgeniya Korneva, Hendrik Blockeel:
Towards Better Evaluation of Multi-target Regression Models. PKDD/ECML Workshops 2020: 353-362 - [d1]Wannes Meert, Kilian Hendrickx, Toon van Craenendonck, Pieter Robberechts, Hendrik Blockeel, Jesse Davis:
DTAIDistance. Zenodo, 2020
- [i22]Kshitij Goyal, Sebastijan Dumancic, Hendrik Blockeel:
Feature Interactions in XGBoost. CoRR abs/2007.05758 (2020)
2010 – 2019
- 2019
- [c107]Sebastijan Dumancic, Tias Guns, Wannes Meert, Hendrik Blockeel:
Learning Relational Representations with Auto-encoding Logic Programs. IJCAI 2019: 6081-6087 - [c106]Jonas Schouterden, Jesse Davis, Hendrik Blockeel:
LazyBum: Decision Tree Learning Using Lazy Propositionalization. ILP 2019: 98-113 - [i21]Sebastijan Dumancic, Tias Guns, Wannes Meert, Hendrik Blockeel:
Learning Relational Representations with Auto-encoding Logic Programs. CoRR abs/1903.12577 (2019) - [i20]Jonas Schouterden, Jesse Davis, Hendrik Blockeel:
LazyBum: Decision tree learning using lazy propositionalization. CoRR abs/1909.05044 (2019) - 2018
- [j48]Hendrik Blockeel:
Declarative data analysis. Int. J. Data Sci. Anal. 6(3): 217-223 (2018) - [j47]Leander Schietgat, Celine Vens, Ricardo Cerri, Carlos N. Fischer, Eduardo P. Costa, Jan Ramon, Claudia M. A. Carareto, Hendrik Blockeel:
A machine learning based framework to identify and classify long terminal repeat retrotransposons. PLoS Comput. Biol. 14(4) (2018) - [c105]Elia Van Wolputte, Evgeniya Korneva, Hendrik Blockeel:
MERCS: Multi-Directional Ensembles of Regression and Classification Trees. AAAI 2018: 4276-4283 - [c104]Evgeniya Korneva, Hendrik Blockeel:
Model Selection for Multi-directional Ensemble of Regression and Classification Trees. BNCAI 2018: 52-64 - [c103]Toon van Craenendonck, Wannes Meert, Sebastijan Dumancic, Hendrik Blockeel:
COBRASTS: A New Approach to Semi-supervised Clustering of Time Series. DS 2018: 179-193 - [c102]Luc De Raedt, Hendrik Blockeel, Samuel Kolb, Stefano Teso, Gust Verbruggen:
Elements of an Automatic Data Scientist. IDA 2018: 3-14 - [c101]Toon van Craenendonck, Sebastijan Dumancic, Elia Van Wolputte, Hendrik Blockeel:
COBRAS: Interactive Clustering with Pairwise Queries. IDA 2018: 353-366 - [c100]Toon van Craenendonck, Wannes Meert, Sebastijan Dumancic, Hendrik Blockeel:
Interactive Time Series Clustering with COBRASTS. ECML/PKDD (3) 2018: 654-657 - [i19]Toon van Craenendonck, Sebastijan Dumancic, Hendrik Blockeel:
COBRA: A Fast and Simple Method for Active Clustering with Pairwise Constraints. CoRR abs/1801.09955 (2018) - [i18]Toon van Craenendonck, Sebastijan Dumancic, Elia Van Wolputte, Hendrik Blockeel:
COBRAS: Fast, Iterative, Active Clustering with Pairwise Constraints. CoRR abs/1803.11060 (2018) - [i17]Toon van Craenendonck, Wannes Meert, Sebastijan Dumancic, Hendrik Blockeel:
COBRAS-TS: A new approach to Semi-Supervised Clustering of Time Series. CoRR abs/1805.00779 (2018) - 2017
- [j46]Toon van Craenendonck, Hendrik Blockeel:
Constraint-based clustering selection. Mach. Learn. 106(9-10): 1497-1521 (2017) - [j45]Sebastijan Dumancic, Hendrik Blockeel:
An expressive dissimilarity measure for relational clustering using neighbourhood trees. Mach. Learn. 106(9-10): 1523-1545 (2017) - [c99]Sebastijan Dumancic, Hendrik Blockeel:
Clustering-Based Relational Unsupervised Representation Learning with an Explicit Distributed Representation. IJCAI 2017: 1631-1637 - [c98]Toon van Craenendonck, Sebastijan Dumancic, Hendrik Blockeel:
COBRA: A Fast and Simple Method for Active Clustering with Pairwise Constraints. IJCAI 2017: 2871-2877 - [c97]Hendrik Blockeel:
PU-learning Disjunctive Concepts in ILP. ILP (Late Breaking Papers) 2017: 6-10 - [c96]Sebastijan Dumancic, Hendrik Blockeel:
Demystifying Relational Latent Representations. ILP 2017: 63-77 - [r13]Hendrik Blockeel:
Bias Specification Language. Encyclopedia of Machine Learning and Data Mining 2017: 125-128 - [r12]Hendrik Blockeel:
Hypothesis Language. Encyclopedia of Machine Learning and Data Mining 2017: 625-629 - [r11]Hendrik Blockeel:
Hypothesis Space. Encyclopedia of Machine Learning and Data Mining 2017: 629-632 - [r10]Soumya Ray, Stephen Scott, Hendrik Blockeel:
Multi-Instance Learning. Encyclopedia of Machine Learning and Data Mining 2017: 864-875 - [r9]Soumya Ray, Stephen Scott, Hendrik Blockeel:
Multiple-Instance Learning. Encyclopedia of Machine Learning and Data Mining 2017: 882-892 - [r8]Hendrik Blockeel:
Observation Language. Encyclopedia of Machine Learning and Data Mining 2017: 917-920 - [r7]Jan Struyf, Hendrik Blockeel:
Relational Learning. Encyclopedia of Machine Learning and Data Mining 2017: 1090-1096 - [i16]Sebastijan Dumancic, Hendrik Blockeel:
Demystifying Relational Latent Representations. CoRR abs/1705.05785 (2017) - 2016
- [j44]Gitte Vanwinckelen, Vinicius Tragante do Ó, Daan Fierens, Hendrik Blockeel:
Instance-level accuracy versus bag-level accuracy in multi-instance learning. Data Min. Knowl. Discov. 30(2): 313-341 (2016) - [j43]Hossein Rahmani, Hendrik Blockeel, Andreas Bender:
Using a Human Drug Network for generating novel hypotheses about drugs. Intell. Data Anal. 20(1): 183-197 (2016) - [c95]Sebastijan Dumancic, Hendrik Blockeel:
An Efficient and Expressive Similarity Measure for Relational Clustering Using Neighbourhood Trees. ECAI 2016: 1674-1675 - [c94]Leonor Becerra-Bonache, Hendrik Blockeel, María Galván, François Jacquenet:
Relational Grounded Language Learning. ECAI 2016: 1764-1765 - [c93]Aäron Verachtert, Hendrik Blockeel, Jesse Davis:
Dynamic Early Stopping for Naive Bayes. IJCAI 2016: 2082-2088 - [c92]Hendrik Blockeel:
Identifying Non-Redundant Literals in Clauses with Uniqueness Propagation. ILP (Short Papers) 2016: 8-13 - [c91]Hendrik Blockeel, Svetlana Valevich:
A Simple Framework for Theta-Subsumption Testing in Prolog. ILP (Short Papers) 2016: 14-19 - [c90]Leonor Becerra-Bonache, Hendrik Blockeel, María Galván, François Jacquenet:
Learning Language Models from Images with ReGLL. ECML/PKDD (3) 2016: 55-58 - [i15]Sebastijan Dumancic, Hendrik Blockeel:
An expressive dissimilarity measure for relational clustering using neighbourhood trees. CoRR abs/1604.08934 (2016) - [i14]Sebastijan Dumancic, Hendrik Blockeel:
Unsupervised Relational Representation Learning via Clustering: Preliminary Results. CoRR abs/1606.08658 (2016) - [i13]Sebastijan Dumancic, Wannes Meert, Hendrik Blockeel:
Theory reconstruction: a representation learning view on predicate invention. CoRR abs/1606.08660 (2016) - [i12]Toon van Craenendonck, Hendrik Blockeel:
Constraint-Based Clustering Selection. CoRR abs/1609.07272 (2016) - 2015
- [j42]Hossein Rahmani, Hendrik Blockeel, Andreas Bender:
Using a Human Disease Network for augmenting prior knowledge about diseases. Intell. Data Anal. 19(4): 897-916 (2015) - [j41]Hendrik Blockeel:
Data Mining: From Procedural to Declarative Approaches. New Gener. Comput. 33(2): 115-135 (2015) - [j40]Maurice Bruynooghe, Hendrik Blockeel, Bart Bogaerts, Broes De Cat, Stef De Pooter, Joachim Jansen, Anthony Labarre, Jan Ramon, Marc Denecker, Sicco Verwer:
Predicate logic as a modeling language: modeling and solving some machine learning and data mining problems with IDP3. Theory Pract. Log. Program. 15(6): 783-817 (2015) - [c89]Leonor Becerra-Bonache, Hendrik Blockeel, María Galván, François Jacquenet:
A First-Order-Logic Based Model for Grounded Language Learning. IDA 2015: 49-60 - [c88]Denny Verbeeck, Hendrik Blockeel:
Slower Can Be Faster: The iRetis Incremental Model Tree Learner. IDA 2015: 322-333 - [c87]Toon van Craenendonck, Hendrik Blockeel:
Limitations of Using Constraint Set Utility in Semi-Supervised Clustering. MetaSel@PKDD/ECML 2015: 27-42 - [c86]Antoine Adam, Hendrik Blockeel:
Dealing with Overlapping Clustering: A Constraint-based Approach to Algorithm Selection. MetaSel@PKDD/ECML 2015: 43-54 - 2014
- [c85]Gitte Vanwinckelen, Hendrik Blockeel:
Look before you leap: Some insights into learner evaluation with cross-validation. SSDM@ECML/PKDD 2014: 3-20 - [e7]Hendrik Blockeel, Matthijs van Leeuwen, Veronica Vinciotti:
Advances in Intelligent Data Analysis XIII - 13th International Symposium, IDA 2014, Leuven, Belgium, October 30 - November 1, 2014. Proceedings. Lecture Notes in Computer Science 8819, Springer 2014, ISBN 978-3-319-12570-1 [contents] - [i11]Nima Taghipour, Daan Fierens, Jesse Davis, Hendrik Blockeel:
Lifted Variable Elimination: Decoupling the Operators from the Constraint Language. CoRR abs/1402.0565 (2014) - 2013
- [j39]Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezný:
Guest editor's introduction: special issue of the ECML PKDD 2013 journal track. Data Min. Knowl. Discov. 27(3): 291-293 (2013) - [j38]Pirooz Shamsinejadbabaki, Mohamad Saraee, Hendrik Blockeel:
Causality-based cost-effective action mining. Intell. Data Anal. 17(6): 1075-1091 (2013) - [j37]Nima Taghipour, Daan Fierens, Jesse Davis, Hendrik Blockeel:
Lifted Variable Elimination: Decoupling the Operators from the Constraint Language. J. Artif. Intell. Res. 47: 393-439 (2013) - [j36]Robert Brijder, Hendrik Blockeel:
On the inference of non-confluent NLC graph grammars. J. Log. Comput. 23(4): 799-814 (2013) - [j35]Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezný:
Guest editor's introduction: special issue of the ECML PKDD 2013 journal track. Mach. Learn. 93(1): 1-3 (2013) - [c84]Nima Taghipour, Daan Fierens, Guy Van den Broeck, Jesse Davis, Hendrik Blockeel:
On the Completeness of Lifted Variable Elimination. StarAI@AAAI 2013 - [c83]Nima Taghipour, Daan Fierens, Guy Van den Broeck, Jesse Davis, Hendrik Blockeel:
Completeness Results for Lifted Variable Elimination. AISTATS 2013: 572-580 - [c82]Pan Hu, Celine Vens, Bart Verstrynge, Hendrik Blockeel:
Generalizing from Example Clusters. Discovery Science 2013: 64-78 - [c81]Denny Verbeeck, Francis Maes, Kurt De Grave, Hendrik Blockeel:
Multi-objective optimization with surrogate trees. GECCO 2013: 679-686 - [c80]Celine Vens, Bart Verstrynge, Hendrik Blockeel:
Semi-supervised Clustering with Example Clusters. KDIR/KMIS 2013: 45-51 - [c79]Eduardo P. Costa, Sicco Verwer, Hendrik Blockeel:
Estimating Prediction Certainty in Decision Trees. IDA 2013: 138-149 - [c78]Nima Taghipour, Jesse Davis, Hendrik Blockeel:
Generalized Counting for Lifted Variable Elimination. ILP 2013: 107-122 - [c77]Nima Taghipour, Jesse Davis, Hendrik Blockeel:
First-order Decomposition Trees. NIPS 2013: 1052-1060 - [c76]Antoine Adam, Hendrik Blockeel, Sander Govers, Abram Aertsen:
SCCQL : A Constraint-Based Clustering System. ECML/PKDD (3) 2013: 681-684 - [p5]Hendrik Blockeel:
Statistical Relational Learning. Handbook on Neural Information Processing 2013: 241-281 - [e6]Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezný:
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 8188, Springer 2013, ISBN 978-3-642-40987-5 [contents] - [e5]Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezný:
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 8189, Springer 2013, ISBN 978-3-642-40990-5 [contents] - [e4]Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezný:
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 8190, Springer 2013, ISBN 978-3-642-40993-6 [contents] - [i10]Nima Taghipour, Jesse Davis, Hendrik Blockeel:
First-Order Decomposition Trees. CoRR abs/1306.0751 (2013) - [i9]Maurice Bruynooghe, Hendrik Blockeel, Bart Bogaerts, Broes De Cat, Stef De Pooter, Joachim Jansen, Anthony Labarre, Jan Ramon, Marc Denecker, Sicco Verwer:
Predicate Logic as a Modeling Language: Modeling and Solving some Machine Learning and Data Mining Problems with IDP3. CoRR abs/1309.6883 (2013) - 2012
- [j34]Hendrik Blockeel, Toon Calders, Élisa Fromont, Bart Goethals, Adriana Prado, Céline Robardet:
An inductive database system based on virtual mining views. Data Min. Knowl. Discov. 24(1): 247-287 (2012) - [j33]Joris Maervoet, Celine Vens, Greet Vanden Berghe, Hendrik Blockeel, Patrick De Causmaecker:
Outlier detection in relational data: A case study in geographical information systems. Expert Syst. Appl. 39(5): 4718-4728 (2012) - [j32]Hossein Rahmani, Hendrik Blockeel, Andreas Bender:
Predicting Genes Involved in Human Cancer Using Network Contextual Information. J. Integr. Bioinform. 9(1) (2012) - [j31]Joaquin Vanschoren, Hendrik Blockeel, Bernhard Pfahringer, Geoffrey Holmes:
Experiment databases - A new way to share, organize and learn from experiments. Mach. Learn. 87(2): 127-158 (2012) - [c75]Hendrik Blockeel, Bart Bogaerts, Maurice Bruynooghe, Broes De Cat, Stef De Pooter, Marc Denecker, Anthony Labarre, Jan Ramon, Sicco Verwer:
Modeling Machine Learning and Data Mining Problems with FO(·). ICLP (Technical Communications) 2012: 14-25 - [c74]Nima Taghipour, Daan Fierens, Jesse Davis, Hendrik Blockeel:
Lifted Variable Elimination with Arbitrary Constraints. AISTATS 2012: 1194-1202 - [i8]Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezný:
A Revised Publication Model for ECML PKDD. CoRR abs/1207.6324 (2012) - [i7]Nima Taghipour, Daan Fierens, Guy Van den Broeck, Jesse Davis, Hendrik Blockeel:
Lifted Variable Elimination: A Novel Operator and Completeness Results. CoRR abs/1208.3809 (2012) - 2011
- [j30]Werner Uwents, Gabriele Monfardini, Hendrik Blockeel, Marco Gori, Franco Scarselli:
Neural networks for relational learning: an experimental comparison. Mach. Learn. 82(3): 315-349 (2011) - [j29]Hendrik Blockeel, Karsten M. Borgwardt, Luc De Raedt, Pedro M. Domingos, Kristian Kersting, Xifeng Yan:
Guest editorial to the special issue on inductive logic programming, mining and learning in graphs and statistical relational learning. Mach. Learn. 83(2): 133-135 (2011) - [c73]Hossein Rahmani, Hendrik Blockeel, Andreas Bender:
Collaboration-Based Function Prediction in Protein-Protein Interaction Networks. IDA 2011: 318-327 - [c72]Beau Piccart, Andy Georges, Hendrik Blockeel, Lieven Eeckhout:
Ranking commercial machines through data transposition. IISWC 2011: 3-14 - [c71]Beau Piccart, Hendrik Blockeel, Andy Georges, Lieven Eeckhout:
Predictive Learning in Two-Way Datasets. ILP (Late Breaking Papers) 2011: 61-68 - [c70]Tijn Witsenburg, Hendrik Blockeel:
K-Means Based Approaches to Clustering Nodes in Annotated Graphs. ISMIS 2011: 346-357 - [c69]Tijn Witsenburg, Hendrik Blockeel:
Improving the Accuracy of Similarity Measures by Using Link Information. ISMIS 2011: 501-512 - [c68]Robert Brijder, Hendrik Blockeel:
Characterizing Compressibility of Disjoint Subgraphs with NLC Grammars. LATA 2011: 167-178 - [i6]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. CoRR abs/1106.1803 (2011) - 2010
- [j28]Leander Schietgat, Celine Vens, Jan Struyf, Hendrik Blockeel, Dragi Kocev, Saso Dzeroski:
Predicting gene function using hierarchical multi-label decision tree ensembles. BMC Bioinform. 11: 2 (2010) - [j27]Kristien Van Loon, Fabian Güiza Grandas, Geert Meyfroidt, Jean-Marie Aerts, Jan Ramon, Hendrik Blockeel, Maurice Bruynooghe, Greta Van den Berghe, Daniel Berckmans:
Prediction of Clinical Conditions after Coronary Bypass Surgery using Dynamic Data Analysis. J. Medical Syst. 34(3): 229-239 (2010) - [j26]Daan Fierens, Jan Ramon, Hendrik Blockeel, Maurice Bruynooghe:
A comparison of pruning criteria for probability trees. Mach. Learn. 78(1-2): 251-285 (2010) - [c67]Celine Vens, Eduardo P. Costa, Hendrik Blockeel:
Top-Down Induction of Phylogenetic Trees. EvoBIO 2010: 62-73 - [c66]Arno J. Knobbe, Hendrik Blockeel, Arne Koopman, Toon Calders, Bas Obladen, Carlos Bosma, Hessel Galenkamp, Eddy Koenders, Joost N. Kok:
InfraWatch: Data Management of Large Systems for Monitoring Infrastructural Performance. IDA 2010: 91-102 - [c65]Wannes Meert, Nima Taghipour, Hendrik Blockeel:
First-Order Bayes-Ball. ECML/PKDD (2) 2010: 369-384 - [c64]Hossein Rahmani, Behrooz Nobakht, Hendrik Blockeel:
Collaboration-based Social Tag Prediction in the Graph of Annotated Web Pages. NyNaK 2010 - [c63]Beau Piccart, Jan Struyf, Hendrik Blockeel:
Alleviating the Sparsity Problem in Collaborative Filtering by Using an Adapted Distance and a Graph-Based Method. SDM 2010: 189-198 - [c62]Hossein Rahmani, Hendrik Blockeel, Andreas Bender:
Predicting the functions of proteins in Protein-Protein Interaction networks from global information. MLSB 2010: 82-97 - [p4]Hendrik Blockeel, Toon Calders, Élisa Fromont, Bart Goethals, Adriana Prado, Céline Robardet:
A Practical Comparative Study Of Data Mining Query Languages. Inductive Databases and Constraint-Based Data Mining 2010: 59-77 - [p3]Hendrik Blockeel, Toon Calders, Élisa Fromont, Adriana Prado, Bart Goethals, Céline Robardet:
Inductive Querying with Virtual Mining Views. Inductive Databases and Constraint-Based Data Mining 2010: 265-287 - [p2]Joaquin Vanschoren, Hendrik Blockeel:
Experiment Databases. Inductive Databases and Constraint-Based Data Mining 2010: 335-361 - [p1]Celine Vens, Leander Schietgat, Jan Struyf, Hendrik Blockeel, Dragi Kocev, Saso Dzeroski:
Predicting Gene Function using Predictive Clustering Trees. Inductive Databases and Constraint-Based Data Mining 2010: 365-387 - [r6]Hendrik Blockeel:
Bias Specification Language. Encyclopedia of Machine Learning 2010: 98-100 - [r5]Hendrik Blockeel:
Hypothesis Language. Encyclopedia of Machine Learning 2010: 507-511 - [r4]Hendrik Blockeel:
Hypothesis Space. Encyclopedia of Machine Learning 2010: 511-513 - [r3]Soumya Ray, Stephen Scott, Hendrik Blockeel:
Multi-Instance Learning. Encyclopedia of Machine Learning 2010: 701-710 - [r2]Hendrik Blockeel:
Observation Language. Encyclopedia of Machine Learning 2010: 733-735 - [r1]Jan Struyf, Hendrik Blockeel:
Relational Learning. Encyclopedia of Machine Learning 2010: 851-857
2000 – 2009
- 2009
- [c61]Wannes Meert, Jan Struyf, Hendrik Blockeel:
CP-Logic Theory Inference with Contextual Variable Elimination and Comparison to BDD Based Inference Methods. ILP 2009: 96-109 - [c60]Kristien Van Loon, Fabian Güiza Grandas, Geert Meyfroidt, Jean-Marie Aerts, Jan Ramon, Hendrik Blockeel, Maurice Bruynooghe, Greta Van den Berghe, Daniel Berckmans:
Dynamic Data Analysis and Data Mining for Prediction of Clinical Stability. MIE 2009: 590-594 - [c59]Joaquin Vanschoren, Hendrik Blockeel:
A Community-Based Platform for Machine Learning Experimentation. ECML/PKDD (2) 2009: 750-754 - [i5]Hendrik Blockeel, Robert Brijder:
Non-Confluent NLC Graph Grammar Inference by Compressing Disjoint Subgraphs. CoRR abs/0901.4876 (2009) - 2008
- [j25]Daan Fierens, Jan Ramon, Maurice Bruynooghe, Hendrik Blockeel:
Learning directed probabilistic logical models: ordering-search versus structure-search. Ann. Math. Artif. Intell. 54(1-3): 99-133 (2008) - [j24]Wannes Meert, Jan Struyf, Hendrik Blockeel:
Learning Ground CP-Logic Theories by Leveraging Bayesian Network Learning Techniques. Fundam. Informaticae 89(1): 131-160 (2008) - [j23]Jan Ramon, Tom Croonenborghs, Daan Fierens, Hendrik Blockeel, Maurice Bruynooghe:
Generalized ordering-search for learning directed probabilistic logical models. Mach. Learn. 70(2-3): 169-188 (2008) - [j22]Hendrik Blockeel, Jude W. Shavlik, Prasad Tadepalli:
Guest editors' introduction: special issue on inductive logic programming (ILP-2007). Mach. Learn. 73(1): 1-2 (2008) - [j21]Celine Vens, Jan Struyf, Leander Schietgat, Saso Dzeroski, Hendrik Blockeel:
Decision trees for hierarchical multi-label classification. Mach. Learn. 73(2): 185-214 (2008) - [c58]Beau Piccart, Jan Struyf, Hendrik Blockeel:
Empirical Asymmetric Selective Transfer in Multi-objective Decision Trees. Discovery Science 2008: 64-75 - [c57]Werner Uwents, Hendrik Blockeel:
A Comparison between Neural Network Methods for Learning Aggregate Functions. Discovery Science 2008: 88-99 - [c56]Leander Schietgat, Jan Ramon, Maurice Bruynooghe, Hendrik Blockeel:
An Efficiently Computable Graph-Based Metric for the Classification of Small Molecules. Discovery Science 2008: 197-209 - [c55]Hendrik Blockeel, Toon Calders, Élisa Fromont, Bart Goethals, Adriana Prado:
Mining Views: Database Views for Data Mining. ICDE 2008: 1608-1611 - [c54]Werner Uwents, Hendrik Blockeel:
Learning Aggregate Functions with Neural Networks Using a Cascade-Correlation Approach. ILP 2008: 315-329 - [c53]Joaquin Vanschoren, Hendrik Blockeel, Bernhard Pfahringer, Geoffrey Holmes:
Organizing the World's Machine Learning Information. ISoLA 2008: 693-708 - [c52]Hendrik Blockeel, Toon Calders, Élisa Fromont, Bart Goethals, Adriana Prado, Céline Robardet:
An inductive database prototype based on virtual mining views. KDD 2008: 1061-1064 - [c51]Hendrik Blockeel:
Exposing the Causal Structure of Processes by Learning CP-Logic Programs. PRICAI 2008: 2 - [e3]Hendrik Blockeel, Jan Ramon, Jude W. Shavlik, Prasad Tadepalli:
Inductive Logic Programming, 17th International Conference, ILP 2007, Corvallis, OR, USA, June 19-21, 2007, Revised Selected Papers. Lecture Notes in Computer Science 4894, Springer 2008, ISBN 978-3-540-78468-5 [contents] - 2007
- [j20]Jan Ramon, Daan Fierens, Fabian Güiza Grandas, Geert Meyfroidt, Hendrik Blockeel, Maurice Bruynooghe, Greta Van den Berghe:
Mining data from intensive care patients. Adv. Eng. Informatics 21(3): 243-256 (2007) - [c50]Anneleen Van Assche, Hendrik Blockeel:
Seeing the Forest Through the Trees: Learning a Comprehensible Model from an Ensemble. ECML 2007: 418-429 - [c49]Daan Fierens, Jan Ramon, Maurice Bruynooghe, Hendrik Blockeel:
Learning Directed Probabilistic Logical Models: Ordering-Search Versus Structure-Search. ECML 2007: 567-574 - [c48]Joaquin Vanschoren, Hendrik Blockeel:
Investigating Classifier Learning Behavior with Experiment Databases. GfKl 2007: 421-428 - [c47]Tom Croonenborghs, Jan Ramon, Hendrik Blockeel, Maurice Bruynooghe:
Online Learning and Exploiting Relational Models in Reinforcement Learning. IJCAI 2007: 726-731 - [c46]Daan Fierens, Jan Ramon, Maurice Bruynooghe, Hendrik Blockeel:
Learning Directed Probabilistic Logical Models Using Ordering-Search. ILP 2007: 24 - [c45]Anneleen Van Assche, Hendrik Blockeel:
Seeing the Forest Through the Trees. ILP 2007: 269-279 - [c44]Hendrik Blockeel, Tijn Witsenburg, Joost N. Kok:
Graphs, Hypergraphs, and Inductive Logic Programming. MLG 2007 - [c43]Hendrik Blockeel, Joaquin Vanschoren:
Experiment Databases: Towards an Improved Experimental Methodology in Machine Learning. PKDD 2007: 6-17 - [c42]Kenneth Hoste, Lieven Eeckhout, Hendrik Blockeel:
Analyzing commercial processor performance numbers for predicting performance of applications of interest. SIGMETRICS 2007: 375-376 - 2006
- [j19]Raymond Kosala, Hendrik Blockeel, Maurice Bruynooghe, Jan Van den Bussche:
Information extraction from structured documents using k-testable tree automaton inference. Data Knowl. Eng. 58(2): 129-158 (2006) - [j18]Celine Vens, Hendrik Blockeel:
A simple regression based heuristic for learning model trees. Intell. Data Anal. 10(3): 215-236 (2006) - [j17]Hendrik Blockeel, David D. Jensen, Stefan Kramer:
Introduction to the special issue on multi-relational data mining and statistical relational learning. Mach. Learn. 62(1-2): 3-5 (2006) - [j16]Anneleen Van Assche, Celine Vens, Hendrik Blockeel, Saso Dzeroski:
First order random forests: Learning relational classifiers with complex aggregates. Mach. Learn. 64(1-3): 149-182 (2006) - [c41]Anneleen Van Assche, Hendrik Blockeel:
Bagging Using Statistical Queries. ECML 2006: 809-816 - [c40]Jan Ramon, Tom Croonenborghs, Daan Fierens, Hendrik Blockeel, Maurice Bruynooghe:
Generalized Ordering-Search for Learning Directed Probabilistic Logical Models. ILP 2006: 40-42 - [c39]Hendrik Blockeel, Wannes Meert:
Towards Learning Non-recursive LPADs by Transforming Them into Bayesian Networks. ILP 2006: 94-108 - [c38]Celine Vens, Jan Ramon, Hendrik Blockeel:
ReMauve: A Relational Model Tree Learner. ILP 2006: 424-438 - [c37]Élisa Fromont, Hendrik Blockeel, Jan Struyf:
Integrating Decision Tree Learning into Inductive Databases. KDID 2006: 81-96 - [c36]Hendrik Blockeel, Leander Schietgat, Jan Struyf, Saso Dzeroski, Amanda Clare:
Decision Trees for Hierarchical Multilabel Classification: A Case Study in Functional Genomics. PKDD 2006: 18-29 - [c35]Celine Vens, Jan Ramon, Hendrik Blockeel:
Refining Aggregate Conditions in Relational Learning. PKDD 2006: 383-394 - 2005
- [j15]Hendrik Blockeel, Saso Dzeroski:
Multi-Relational Data Mining 2005: workshop report. SIGKDD Explor. 7(2): 126-128 (2005) - [c34]Daan Fierens, Hendrik Blockeel, Maurice Bruynooghe, Jan Ramon:
Logical Bayesian Networks and Their Relation to Other Probabilistic Logical Models. BNAIC 2005: 343-344 - [c33]Daan Fierens, Jan Ramon, Hendrik Blockeel, Maurice Bruynooghe:
A Comparison of Approaches for Learning Probability Trees. ECML 2005: 556-563 - [c32]Jan Struyf, Saso Dzeroski, Hendrik Blockeel, Amanda Clare:
Hierarchical Multi-classification with Predictive Clustering Trees in Functional Genomics. EPIA 2005: 272-283 - [c31]Hendrik Blockeel, David Page, Ashwin Srinivasan:
Multi-instance tree learning. ICML 2005: 57-64 - [c30]Daan Fierens, Hendrik Blockeel, Maurice Bruynooghe, Jan Ramon:
Logical Bayesian Networks and Their Relation to Other Probabilistic Logical Models. ILP 2005: 121-135 - [c29]Werner Uwents, Hendrik Blockeel:
Classifying Relational Data with Neural Networks. ILP 2005: 384-396 - [c28]Hendrik Blockeel:
Experiment Databases: A Novel Methodology for Experimental Research. KDID 2005: 72-85 - 2004
- [j14]Hendrik Blockeel, Saso Dzeroski, Boris Kompare, Stefan Kramer, Bernhard Pfahringer, Wim Van Laer:
Experiments In Predicting Biodegradability. Appl. Artif. Intell. 18(2): 157-181 (2004) - [j13]Jan Struyf, Jan Ramon, Maurice Bruynooghe, Sofie Verbaeten, Hendrik Blockeel:
Compact Representation of Knowledge Bases in Inductive Logic Programming. Mach. Learn. 57(3): 305-333 (2004) - [j12]Saso Dzeroski, Hendrik Blockeel:
Multi-relational data mining 2004: workshop report. SIGKDD Explor. 6(2): 140-141 (2004) - [c27]Celine Vens, Anneleen Van Assche, Hendrik Blockeel, Saso Dzeroski:
First Order Random Forests with Complex Aggregates. ILP 2004: 323-340 - 2003
- [j11]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. J. Mach. Learn. Res. 4: 465-491 (2003) - [j10]Hendrik Blockeel, Michèle Sebag:
Scalability and efficiency in multi-relational data mining. SIGKDD Explor. 5(1): 17-30 (2003) - [c26]Nico Jacobs, Hendrik Blockeel:
User Modeling with Sequential Data. HCI (4) 2003: 557-561 - [c25]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 - [c24]Jan Struyf, Hendrik Blockeel:
Query Optimization in Inductive Logic Programming by Reordering Literals. ILP 2003: 329-346 - [e2]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. Lecture Notes in Computer Science 2837, Springer 2003, ISBN 3-540-20121-1 [contents] - [e1]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. Lecture Notes in Computer Science 2838, Springer 2003, ISBN 3-540-20085-1 [contents] - 2002
- [j9]Hendrik Blockeel, Jan Struyf:
Deriving biased classifiers for better ROC performance. Informatica (Slovenia) 26(1) (2002) - [j8]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. 16: 135-166 (2002) - [j7]Hendrik Blockeel, Jan Struyf:
Efficient Algorithms for Decision Tree Cross-validation. J. Mach. Learn. Res. 3: 621-650 (2002) - [c23]Ljupco Todorovski, Hendrik Blockeel, Saso Dzeroski:
Ranking with Predictive Clustering Trees. ECML 2002: 444-455 - [c22]Jan Struyf, Jan Ramon, Hendrik Blockeel:
Compact Representation of Knowledge Bases in ILP. ILP 2002: 254-269 - [c21]Raymond Kosala, Jan Van den Bussche, Maurice Bruynooghe, Hendrik Blockeel:
Information Extraction in Structured Documents Using Tree Automata Induction. PKDD 2002: 299-310 - 2001
- [c20]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 - [c19]Hendrik Blockeel, Jan Struyf:
Efficient algorithms for decision tree cross-validation. ICML 2001: 11-18 - [c18]Nico Jacobs, Hendrik Blockeel:
From Shell Logs to Shell Scripts. ILP 2001: 80-90 - [c17]Jan Struyf, Hendrik Blockeel:
Efficient Cross-Validation in ILP. ILP 2001: 228-239 - [c16]Hendrik Blockeel, Johannes Fürnkranz, Alexia Prskawetz, Francesco C. Billari:
Detecting Temporal Change in Event Sequences: An Application to Demographic Data. PKDD 2001: 29-41 - [c15]Nico Jacobs, Hendrik Blockeel:
The Learning Shell: Automated Macro Construction. User Modeling 2001: 34-43 - [i4]Hendrik Blockeel, Jan Struyf:
Efficient algorithms for decision tree cross-validation. CoRR cs.LG/0110036 (2001) - 2000
- [j6]Raymond Kosala, Hendrik Blockeel:
Web Mining Research: A Survey. SIGKDD Explor. 2(1): 1-15 (2000) - [c14]Jan Ramon, Tom Francis, Hendrik Blockeel:
Learning a Go Heuristic with TILDE. Computers and Games 2000: 151-169 - [c13]Hendrik Blockeel, Luc Dehaspe, Bart Demoen, Gerda Janssens, Jan Ramon, Henk Vandecasteele:
Executing Query Packs in ILP. ILP 2000: 60-77 - [c12]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 - [c11]Arno J. Knobbe, Arno Siebes, Hendrik Blockeel, Danïel van der Wallen:
Multi-Relational Data Mining, Using UML for ILP. PKDD 2000: 1-12 - [i3]Hendrik Blockeel, Luc De Raedt, Jan Ramon:
Top-down induction of clustering trees. CoRR cs.LG/0011032 (2000) - [i2]Raymond Kosala, Hendrik Blockeel:
Web Mining Research: A Survey. CoRR cs.LG/0011033 (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
- [j5]Hendrik Blockeel:
Top-Down Induction of First Order Logical Decision Trees. AI Commun. 12(1-2): 119-120 (1999) - [j4]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) - [c10]Saso Dzeroski, Hendrik Blockeel, Boris Kompare, Stefan Kramer, Bernhard Pfahringer, Wim Van Laer:
Experiments in Predicting Biodegradability. ILP 1999: 80-91 - [c9]Hendrik Blockeel, Saso Dzeroski, Jasna Grbovic:
Simultaneous Prediction of Mulriple Chemical Parameters of River Water Quality with TILDE. PKDD 1999: 32-40 - [c8]Luc De Raedt, Hendrik Blockeel:
Relational Learning and Inductive Logic Programming Made Easy Abstract of Tutorial. PKDD 1999: 590 - 1998
- [j3]Saso Dzeroski, Steffen Schulze-Kremer, Karsten R. Heidtke, Karsten Siems, Dietrich Wettschereck, Hendrik Blockeel:
Diterpene Structure Elucidation from 13CNMR Spectra with Inductive Logic Programming. Appl. Artif. Intell. 12(5): 363-383 (1998) - [j2]Hendrik Blockeel, Luc De Raedt:
Isidd: An Interactive System for Inductive Database Design. Appl. Artif. Intell. 12(5): 385-420 (1998) - [j1]Hendrik Blockeel, Luc De Raedt:
Top-Down Induction of First-Order Logical Decision Trees. Artif. Intell. 101(1-2): 285-297 (1998) - [c7]Hendrik Blockeel, Luc De Raedt, Jan Ramon:
Top-Down Induction of Clustering Trees. ICML 1998: 55-63 - [c6]Saso Dzeroski, Luc De Raedt, Hendrik Blockeel:
Relational Reinforcement Learning. ICML 1998: 136-143 - [c5]Saso Dzeroski, Luc De Raedt, Hendrik Blockeel:
Relational Reinforcement Learning. ILP 1998: 11-22 - 1997
- [c4]Hendrik Blockeel, Luc De Raedt:
Lookahead and Discretization in ILP. ILP 1997: 77-84 - [c3]Luc De Raedt, Hendrik Blockeel:
Using Logical Decision Trees for Clustering. ILP 1997: 133-140 - 1996
- [c2]Hendrik Blockeel, Luc De Raedt:
Relational Knowledge Discovery in Databases. Inductive Logic Programming Workshop 1996: 199-211 - [c1]Hendrik Blockeel, Luc De Raedt:
Inductive Database Design. ISMIS 1996: 376-385
Coauthor Index
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