Relational Knowledge Discovery in Databases. - Hendrik Blockeel; Luc De Raedt (Inductive Logic Programming Workshop, 1996)

Inductive Database Design. - Hendrik Blockeel; Luc De Raedt (ISMIS, 1996)

Lookahead and Discretization in ILP. - Hendrik Blockeel; Luc De Raedt (ILP, 1997)

Using Logical Decision Trees for Clustering. - Luc De Raedt; Hendrik Blockeel (ILP, 1997)

Top-Down Induction of Clustering Trees. - Hendrik Blockeel; Luc De Raedt; Jan Ramon (ICML, 1998)

Relational Reinforcement Learning. - Saso Dzeroski; Luc De Raedt; Hendrik Blockeel (ICML, 1998)

Isidd: An Interactive System for Inductive Database Design. - Hendrik Blockeel; Luc De Raedt (Appl. Artif. Intell., 1998)

Diterpene Structure Elucidation from 13CNMR Spectra with Inductive Logic Programming. - Saso Dzeroski; Steffen Schulze-Kremer; Karsten R. Heidtke; Karsten Siems; Dietrich Wettschereck; Hendrik Blockeel (Appl. Artif. Intell., 1998)

Top-Down Induction of First-Order Logical Decision Trees. - Hendrik Blockeel; Luc De Raedt (Artif. Intell., 1998)

Simultaneous Prediction of Mulriple Chemical Parameters of River Water Quality with TILDE. - Hendrik Blockeel; Saso Dzeroski; Jasna Grbovic (PKDD, 1999)

Relational Learning and Inductive Logic Programming Made Easy Abstract of Tutorial. - Luc De Raedt; Hendrik Blockeel (PKDD, 1999)

Top-Down Induction of First Order Logical Decision Trees. - Hendrik Blockeel (AI Commun., 1999)

Scaling Up Inductive Logic Programming by Learning from Interpretations. - Hendrik Blockeel; Luc De Raedt; Nico Jacobs; Bart Demoen (Data Min. Knowl. Discov., 1999)

Learning a Go Heuristic with TILDE. - Jan Ramon; Tom Francis; Hendrik Blockeel (Computers and Games, 2000)

Executing Query Packs in ILP. - Hendrik Blockeel; Luc Dehaspe; Bart Demoen; Gerda Janssens; Jan Ramon; Henk Vandecasteele (ILP, 2000)

Two Advanced Transormations for Improving the Efficiency of an ILP system. - Hendrik Blockeel; Bart Demoen; Gerda Janssens; Henk Vandecasteele; Wim Van Laer (ILP Work-in-progress reports, 2000)

Multi-Relational Data Mining, Using UML for ILP. - Arno J. Knobbe; Arno Siebes; Hendrik Blockeel; Danïel van der Wallen (PKDD, 2000)

Web Mining Research: A Survey. - Raymond Kosala; Hendrik Blockeel (SIGKDD Explor., 2000)

Speeding Up Relational Reinforcement Learning through the Use of an Incremental First Order Decision Tree Learner. - Kurt Driessens; Jan Ramon; Hendrik Blockeel (ECML, 2001)

From Shell Logs to Shell Scripts. - Nico Jacobs; Hendrik Blockeel (ILP, 2001)

Efficient Cross-Validation in ILP. - Jan Struyf; Hendrik Blockeel (ILP, 2001)

Detecting Temporal Change in Event Sequences: An Application to Demographic Data. - Hendrik Blockeel; Johannes Fürnkranz; Alexia Prskawetz; Francesco C. Billari (PKDD, 2001)

The Learning Shell: Automated Macro Construction. - Nico Jacobs; Hendrik Blockeel (User Modeling, 2001)

Ranking with Predictive Clustering Trees. - Ljupco Todorovski; Hendrik Blockeel; Saso Dzeroski (ECML, 2002)

Compact Representation of Knowledge Bases in ILP. - Jan Struyf; Jan Ramon; Hendrik Blockeel (ILP, 2002)

Information Extraction in Structured Documents Using Tree Automata Induction. - Raymond Kosala; Jan Van den Bussche; Maurice Bruynooghe; Hendrik Blockeel (PKDD, 2002)

Deriving biased classifiers for better ROC performance. - Hendrik Blockeel; Jan Struyf (Informatica (Slovenia), 2002)

Improving the Efficiency of Inductive Logic Programming Through the Use of Query Packs. - Hendrik Blockeel; Luc Dehaspe; Bart Demoen; Gerda Janssens; Jan Ramon; Henk Vandecasteele (J. Artif. Intell. Res., 2002)

Efficient Algorithms for Decision Tree Cross-validation. - Hendrik Blockeel; Jan Struyf (J. Mach. Learn. Res., 2002)

User Modeling with Sequential Data. - Nico Jacobs; Hendrik Blockeel (HCI (4), 2003)

Information Extraction from Web Documents Based on Local Unranked Tree Automaton Inference. - Raymond Kosala; Maurice Bruynooghe; Jan Van den Bussche; Hendrik Blockeel (IJCAI, 2003)

Query Optimization in Inductive Logic Programming by Reordering Literals. - Jan Struyf; Hendrik Blockeel (ILP, 2003)

Query Transformations for Improving the Efficiency of ILP Systems. - Vítor Santos Costa; Ashwin Srinivasan 001; Rui Camacho; Hendrik Blockeel; Bart Demoen; Gerda Janssens; Jan Struyf; Henk Vandecasteele; Wim Van Laer (J. Mach. Learn. Res., 2003)

Scalability and efficiency in multi-relational data mining. - Hendrik Blockeel; Michèle Sebag (SIGKDD Explor., 2003)

First Order Random Forests with Complex Aggregates. - Celine Vens; Anneleen Van Assche; Hendrik Blockeel; Saso Dzeroski (ILP, 2004)

Experiments In Predicting Biodegradability. - Hendrik Blockeel; Saso Dzeroski; Boris Kompare; Stefan Kramer 001; Bernhard Pfahringer; Wim Van Laer (Appl. Artif. Intell., 2004)

Compact Representation of Knowledge Bases in Inductive Logic Programming. - Jan Struyf; Jan Ramon; Maurice Bruynooghe; Sofie Verbaeten; Hendrik Blockeel (Mach. Learn., 2004)

Multi-relational data mining 2004: workshop report. - Saso Dzeroski; Hendrik Blockeel (SIGKDD Explor., 2004)

Logical Bayesian Networks and Their Relation to Other Probabilistic Logical Models. - Daan Fierens; Hendrik Blockeel; Maurice Bruynooghe; Jan Ramon (BNAIC, 2005)

A Comparison of Approaches for Learning Probability Trees. - Daan Fierens; Jan Ramon; Hendrik Blockeel; Maurice Bruynooghe (ECML, 2005)

Hierarchical Multi-classification with Predictive Clustering Trees in Functional Genomics. - Jan Struyf; Saso Dzeroski; Hendrik Blockeel; Amanda Clare (EPIA, 2005)

Multi-instance tree learning. - Hendrik Blockeel; David Page; Ashwin Srinivasan 001 (ICML, 2005)

Classifying Relational Data with Neural Networks. - Werner Uwents; Hendrik Blockeel (ILP, 2005)

Experiment Databases: A Novel Methodology for Experimental Research. - Hendrik Blockeel (KDID, 2005)

Multi-Relational Data Mining 2005: workshop report. - Hendrik Blockeel; Saso Dzeroski (SIGKDD Explor., 2005)

Bagging Using Statistical Queries. - Anneleen Van Assche; Hendrik Blockeel (ECML, 2006)

Towards Learning Non-recursive LPADs by Transforming Them into Bayesian Networks. - Hendrik Blockeel; Wannes Meert (ILP, 2006)

ReMauve: A Relational Model Tree Learner. - Celine Vens; Jan Ramon; Hendrik Blockeel (ILP, 2006)

Integrating Decision Tree Learning into Inductive Databases. - Élisa Fromont; Hendrik Blockeel; Jan Struyf (KDID, 2006)

Decision Trees for Hierarchical Multilabel Classification: A Case Study in Functional Genomics. - Hendrik Blockeel; Leander Schietgat; Jan Struyf; Saso Dzeroski; Amanda Clare (PKDD, 2006)

Refining Aggregate Conditions in Relational Learning. - Celine Vens; Jan Ramon; Hendrik Blockeel (PKDD, 2006)

Information extraction from structured documents using k-testable tree automaton inference. - Raymond Kosala; Hendrik Blockeel; Maurice Bruynooghe; Jan Van den Bussche (Data Knowl. Eng., 2006)

A simple regression based heuristic for learning model trees. - Celine Vens; Hendrik Blockeel (Intell. Data Anal., 2006)

First order random forests: Learning relational classifiers with complex aggregates. - Anneleen Van Assche; Celine Vens; Hendrik Blockeel; Saso Dzeroski (Mach. Learn., 2006)

Introduction to the special issue on multi-relational data mining and statistical relational learning. - Hendrik Blockeel; David D. Jensen; Stefan Kramer 001 (Mach. Learn., 2006)

Seeing the Forest Through the Trees: Learning a Comprehensible Model from an Ensemble. - Anneleen Van Assche; Hendrik Blockeel (ECML, 2007)

Investigating Classifier Learning Behavior with Experiment Databases. - Joaquin Vanschoren; Hendrik Blockeel (GfKl, 2007)

Online Learning and Exploiting Relational Models in Reinforcement Learning. - Tom Croonenborghs; Jan Ramon; Hendrik Blockeel; Maurice Bruynooghe (IJCAI, 2007)

Seeing the Forest Through the Trees. - Anneleen Van Assche; Hendrik Blockeel (ILP, 2007)

Learning Directed Probabilistic Logical Models Using Ordering-Search. - Daan Fierens; Jan Ramon; Maurice Bruynooghe; Hendrik Blockeel (ILP, 2007)

Graphs, Hypergraphs, and Inductive Logic Programming. - Hendrik Blockeel; Tijn Witsenburg; Joost N. Kok (MLG, 2007)

Experiment Databases: Towards an Improved Experimental Methodology in Machine Learning. - Hendrik Blockeel; Joaquin Vanschoren (PKDD, 2007)

Analyzing commercial processor performance numbers for predicting performance of applications of interest. - Kenneth Hoste; Lieven Eeckhout; Hendrik Blockeel (SIGMETRICS, 2007)

Mining data from intensive care patients. - Jan Ramon; Daan Fierens; Fabian Güiza Grandas; Geert Meyfroidt; Hendrik Blockeel; Maurice Bruynooghe; Greta Van den Berghe (Adv. Eng. Informatics, 2007)

Empirical Asymmetric Selective Transfer in Multi-objective Decision Trees. - Beau Piccart; Jan Struyf; Hendrik Blockeel (Discovery Science, 2008)

An Efficiently Computable Graph-Based Metric for the Classification of Small Molecules. - Leander Schietgat; Jan Ramon; Maurice Bruynooghe; Hendrik Blockeel (Discovery Science, 2008)

A Comparison between Neural Network Methods for Learning Aggregate Functions. - Werner Uwents; Hendrik Blockeel (Discovery Science, 2008)

Mining Views: Database Views for Data Mining. - Hendrik Blockeel; Toon Calders; Élisa Fromont; Bart Goethals; Adriana Prado (ICDE, 2008)

Learning Aggregate Functions with Neural Networks Using a Cascade-Correlation Approach. - Werner Uwents; Hendrik Blockeel (ILP, 2008)

Organizing the World's Machine Learning Information. - Joaquin Vanschoren; Hendrik Blockeel; Bernhard Pfahringer; Geoffrey Holmes 001 (ISoLA, 2008)

An inductive database prototype based on virtual mining views. - Hendrik Blockeel; Toon Calders; Élisa Fromont; Bart Goethals; Adriana Prado; Céline Robardet (KDD, 2008)

Induction of Node Label Controlled Graph Grammar Rules. - Hendrik Blockeel; Siegfried Nijssen (MLG@ICML, 2008)

Exposing the Causal Structure of Processes by Learning CP-Logic Programs. - Hendrik Blockeel (PRICAI, 2008)

Learning directed probabilistic logical models: ordering-search versus structure-search. - Daan Fierens; Jan Ramon; Maurice Bruynooghe; Hendrik Blockeel (Ann. Math. Artif. Intell., 2008)

Learning Ground CP-Logic Theories by Leveraging Bayesian Network Learning Techniques. - Wannes Meert; Jan Struyf; Hendrik Blockeel (Fundam. Informaticae, 2008)

Guest editors' introduction: special issue on inductive logic programming (ILP-2007). - Hendrik Blockeel; Jude W. Shavlik; Prasad Tadepalli (Mach. Learn., 2008)

Generalized ordering-search for learning directed probabilistic logical models. - Jan Ramon; Tom Croonenborghs; Daan Fierens; Hendrik Blockeel; Maurice Bruynooghe (Mach. Learn., 2008)

Decision trees for hierarchical multi-label classification. - Celine Vens; Jan Struyf; Leander Schietgat; Saso Dzeroski; Hendrik Blockeel (Mach. Learn., 2008)

CP-Logic Theory Inference with Contextual Variable Elimination and Comparison to BDD Based Inference Methods. - Wannes Meert; Jan Struyf; Hendrik Blockeel (ILP, 2009)

Dynamic Data Analysis and Data Mining for Prediction of Clinical Stability. - Kristien Van Loon; Fabian Güiza Grandas; Geert Meyfroidt; Jean-Marie Aerts; Jan Ramon; Hendrik Blockeel; Maurice Bruynooghe; Greta Van den Berghe; Daniel Berckmans (MIE, 2009)

First-Order Bayes-Ball for CP-Logic. - Nima Taghipour; Wannes Meert; Jan Struyf; Hendrik Blockeel (MLG/SRL@ILP, 2009)

A Community-Based Platform for Machine Learning Experimentation. - Joaquin Vanschoren; Hendrik Blockeel (ECML/PKDD (2), 2009)

Non-Confluent NLC Graph Grammar Inference by Compressing Disjoint Subgraphs. - Hendrik Blockeel; Robert Brijder (CoRR, 2009)

A Practical Comparative Study Of Data Mining Query Languages. - Hendrik Blockeel; Toon Calders; Élisa Fromont; Bart Goethals; Adriana Prado; Céline Robardet (Inductive Databases and Constraint-Based Data Mining, 2010)

Inductive Querying with Virtual Mining Views. - Hendrik Blockeel; Toon Calders; Élisa Fromont; Adriana Prado; Bart Goethals; Céline Robardet (Inductive Databases and Constraint-Based Data Mining, 2010)

Experiment Databases. - Joaquin Vanschoren; Hendrik Blockeel (Inductive Databases and Constraint-Based Data Mining, 2010)

Predicting Gene Function using Predictive Clustering Trees. - Celine Vens; Leander Schietgat; Jan Struyf; Hendrik Blockeel; Dragi Kocev; Saso Dzeroski (Inductive Databases and Constraint-Based Data Mining, 2010)

Top-Down Induction of Phylogenetic Trees. - Celine Vens; Eduardo P. Costa; Hendrik Blockeel (EvoBIO, 2010)

InfraWatch: Data Management of Large Systems for Monitoring Infrastructural Performance. - Arno J. Knobbe; Hendrik Blockeel; Arne Koopman; Toon Calders; Bas Obladen; Carlos Bosma; Hessel Galenkamp; Eddy Koenders; Joost N. Kok (IDA, 2010)

First-Order Bayes-Ball. - Wannes Meert; Nima Taghipour; Hendrik Blockeel (ECML/PKDD (2), 2010)

Collaboration-based Social Tag Prediction in the Graph of Annotated Web Pages. - Hossein Rahmani 002; Behrooz Nobakht; Hendrik Blockeel (NyNaK, 2010)

Alleviating the Sparsity Problem in Collaborative Filtering by Using an Adapted Distance and a Graph-Based Method. - Beau Piccart; Jan Struyf; Hendrik Blockeel (SDM, 2010)

Predicting gene function using hierarchical multi-label decision tree ensembles. - Leander Schietgat; Celine Vens; Jan Struyf; Hendrik Blockeel; Dragi Kocev; Saso Dzeroski (BMC Bioinform., 2010)

Predicting the functions of proteins in Protein-Protein Interaction networks from global information. - Hossein Rahmani 002; Hendrik Blockeel; Andreas Bender 002 (MLSB, 2010)

Prediction of Clinical Conditions after Coronary Bypass Surgery using Dynamic Data Analysis. - Kristien Van Loon; Fabian Güiza Grandas; Geert Meyfroidt; Jean-Marie Aerts; Jan Ramon; Hendrik Blockeel; Maurice Bruynooghe; Greta Van den Berghe; Daniel Berckmans (J. Medical Syst., 2010)

A comparison of pruning criteria for probability trees. - Daan Fierens; Jan Ramon; Hendrik Blockeel; Maurice Bruynooghe (Mach. Learn., 2010)

Bias Specification Language. - Hendrik Blockeel (Encyclopedia of Machine Learning, 2010)

Hypothesis Language. - Hendrik Blockeel (Encyclopedia of Machine Learning, 2010)

Hypothesis Space. - Hendrik Blockeel (Encyclopedia of Machine Learning, 2010)

Observation Language. - Hendrik Blockeel (Encyclopedia of Machine Learning, 2010)

Multi-Instance Learning. - Soumya Ray; Stephen Scott 001; Hendrik Blockeel (Encyclopedia of Machine Learning, 2010)

Relational Learning. - Jan Struyf; Hendrik Blockeel (Encyclopedia of Machine Learning, 2010)

Collaboration-Based Function Prediction in Protein-Protein Interaction Networks. - Hossein Rahmani 002; Hendrik Blockeel; Andreas Bender 002 (IDA, 2011)

Ranking commercial machines through data transposition. - Beau Piccart; Andy Georges; Hendrik Blockeel; Lieven Eeckhout (IISWC, 2011)

Predictive Learning in Two-Way Datasets. - Beau Piccart; Hendrik Blockeel; Andy Georges; Lieven Eeckhout (ILP (Late Breaking Papers), 2011)

K-Means Based Approaches to Clustering Nodes in Annotated Graphs. - Tijn Witsenburg; Hendrik Blockeel (ISMIS, 2011)

Improving the Accuracy of Similarity Measures by Using Link Information. - Tijn Witsenburg; Hendrik Blockeel (ISMIS, 2011)

Characterizing Compressibility of Disjoint Subgraphs with NLC Grammars. - Robert Brijder; Hendrik Blockeel (LATA, 2011)

Guest editorial to the special issue on inductive logic programming, mining and learning in graphs and statistical relational learning. - Hendrik Blockeel; Karsten M. Borgwardt; Luc De Raedt; Pedro M. Domingos; Kristian Kersting; Xifeng Yan (Mach. Learn., 2011)

Neural networks for relational learning: an experimental comparison. - Werner Uwents; Gabriele Monfardini; Hendrik Blockeel; Marco Gori; Franco Scarselli (Mach. Learn., 2011)

Modeling Machine Learning and Data Mining Problems with FO(·). - Hendrik Blockeel; Bart Bogaerts 001; Maurice Bruynooghe; Broes De Cat; Stef De Pooter; Marc Denecker; Anthony Labarre; Jan Ramon; Sicco Verwer (ICLP (Technical Communications), 2012)

A Revised Publication Model for ECML PKDD - Hendrik Blockeel; Kristian Kersting; Siegfried Nijssen; Filip Zelezný (CoRR, 2012)

Lifted Variable Elimination: A Novel Operator and Completeness Results - Nima Taghipour; Daan Fierens; Guy Van den Broeck; Jesse Davis; Hendrik Blockeel (CoRR, 2012)

An inductive database system based on virtual mining views. - Hendrik Blockeel; Toon Calders; Élisa Fromont; Bart Goethals; Adriana Prado; Céline Robardet (Data Min. Knowl. Discov., 2012)

Outlier detection in relational data: A case study in geographical information systems. - Joris Maervoet; Celine Vens; Greet Vanden Berghe; Hendrik Blockeel; Patrick De Causmaecker (Expert Syst. Appl., 2012)

Predicting Genes Involved in Human Cancer Using Network Contextual Information. - Hossein Rahmani 002; Hendrik Blockeel; Andreas Bender 002 (J. Integr. Bioinform., 2012)

Lifted Variable Elimination with Arbitrary Constraints. - Nima Taghipour; Daan Fierens; Jesse Davis; Hendrik Blockeel (AISTATS, 2012)

Experiment databases - A new way to share, organize and learn from experiments. - Joaquin Vanschoren; Hendrik Blockeel; Bernhard Pfahringer; Geoffrey Holmes 001 (Mach. Learn., 2012)

On the Completeness of Lifted Variable Elimination. - Nima Taghipour; Daan Fierens; Guy Van den Broeck; Jesse Davis; Hendrik Blockeel (StarAI@AAAI, 2013)

Completeness Results for Lifted Variable Elimination. - Nima Taghipour; Daan Fierens; Guy Van den Broeck; Jesse Davis; Hendrik Blockeel (AISTATS, 2013)

Generalizing from Example Clusters. - Pan Hu; Celine Vens; Bart Verstrynge; Hendrik Blockeel (Discovery Science, 2013)

Multi-objective optimization with surrogate trees. - Denny Verbeeck; Francis Maes; Kurt De Grave; Hendrik Blockeel (GECCO, 2013)

Semi-supervised Clustering with Example Clusters. - Celine Vens; Bart Verstrynge; Hendrik Blockeel (KDIR/KMIS, 2013)

Estimating Prediction Certainty in Decision Trees. - Eduardo P. Costa; Sicco Verwer; Hendrik Blockeel (IDA, 2013)

Generalized Counting for Lifted Variable Elimination. - Nima Taghipour; Jesse Davis; Hendrik Blockeel (ILP, 2013)

First-order Decomposition Trees. - Nima Taghipour; Jesse Davis; Hendrik Blockeel (NIPS, 2013)

SCCQL : A Constraint-Based Clustering System. - Antoine Adam; Hendrik Blockeel; Sander Govers; Abram Aertsen (ECML/PKDD (3), 2013)

Predicate Logic as a Modeling Language: Modeling and Solving some Machine Learning and Data Mining Problems with IDP3. - Maurice Bruynooghe; Hendrik Blockeel; Bart Bogaerts 001; Broes De Cat; Stef De Pooter; Joachim Jansen; Anthony Labarre; Jan Ramon; Marc Denecker; Sicco Verwer (CoRR, 2013)

Causality-based cost-effective action mining. - Pirooz Shamsinejadbabaki; Mohamad Saraee; Hendrik Blockeel (Intell. Data Anal., 2013)

Lifted Variable Elimination: Decoupling the Operators from the Constraint Language. - Nima Taghipour; Daan Fierens; Jesse Davis; Hendrik Blockeel (J. Artif. Intell. Res., 2013)

On the inference of non-confluent NLC graph grammars. - Robert Brijder; Hendrik Blockeel (J. Log. Comput., 2013)

Guest editor's introduction: special issue of the ECML PKDD 2013 journal track. - Hendrik Blockeel; Kristian Kersting; Siegfried Nijssen; Filip Zelezný (Mach. Learn., 2013)

Statistical Relational Learning. - Hendrik Blockeel (Handbook on Neural Information Processing, 2013)

Look before you leap: Some insights into learner evaluation with cross-validation. - Gitte Vanwinckelen; Hendrik Blockeel (SSDM@ECML/PKDD, 2014)

A First-Order-Logic Based Model for Grounded Language Learning. - Leonor Becerra-Bonache; Hendrik Blockeel; María Galván; François Jacquenet (IDA, 2015)

Slower Can Be Faster: The iRetis Incremental Model Tree Learner. - Denny Verbeeck; Hendrik Blockeel (IDA, 2015)

Dealing with Overlapping Clustering: A Constraint-based Approach to Algorithm Selection. - Antoine Adam; Hendrik Blockeel (MetaSel@PKDD/ECML, 2015)

Limitations of Using Constraint Set Utility in Semi-Supervised Clustering. - Toon van Craenendonck; Hendrik Blockeel (MetaSel@PKDD/ECML, 2015)

Using a Human Disease Network for augmenting prior knowledge about diseases. - Hossein Rahmani 002; Hendrik Blockeel; Andreas Bender 002 (Intell. Data Anal., 2015)

Data Mining: From Procedural to Declarative Approaches. - Hendrik Blockeel (New Gener. Comput., 2015)

Predicate logic as a modeling language: modeling and solving some machine learning and data mining problems with IDP3. - Maurice Bruynooghe; Hendrik Blockeel; Bart Bogaerts 001; Broes De Cat; Stef De Pooter; Joachim Jansen; Anthony Labarre; Jan Ramon; Marc Denecker; Sicco Verwer (Theory Pract. Log. Program., 2015)

Relational Grounded Language Learning. - Leonor Becerra-Bonache; Hendrik Blockeel; María Galván; François Jacquenet (ECAI, 2016)

An Efficient and Expressive Similarity Measure for Relational Clustering Using Neighbourhood Trees. - Sebastijan Dumancic; Hendrik Blockeel (ECAI, 2016)

Dynamic Early Stopping for Naive Bayes. - Aäron Verachtert; Hendrik Blockeel; Jesse Davis (IJCAI, 2016)

Identifying Non-Redundant Literals in Clauses with Uniqueness Propagation. - Hendrik Blockeel (ILP (Short Papers), 2016)

A Simple Framework for Theta-Subsumption Testing in Prolog. - Hendrik Blockeel; Svetlana Valevich (ILP (Short Papers), 2016)

Learning Language Models from Images with ReGLL. - Leonor Becerra-Bonache; Hendrik Blockeel; María Galván; François Jacquenet (ECML/PKDD (3), 2016)

Unsupervised Relational Representation Learning via Clustering: Preliminary Results. - Sebastijan Dumancic; Hendrik Blockeel (CoRR, 2016)

Theory reconstruction: a representation learning view on predicate invention. - Sebastijan Dumancic; Wannes Meert; Hendrik Blockeel (CoRR, 2016)

Instance-level accuracy versus bag-level accuracy in multi-instance learning. - Gitte Vanwinckelen; Vinicius Tragante do Ó; Daan Fierens; Hendrik Blockeel (Data Min. Knowl. Discov., 2016)

Using a Human Drug Network for generating novel hypotheses about drugs. - Hossein Rahmani 002; Hendrik Blockeel; Andreas Bender 002 (Intell. Data Anal., 2016)

COBRA: A Fast and Simple Method for Active Clustering with Pairwise Constraints. - Toon van Craenendonck; Sebastijan Dumancic; Hendrik Blockeel (IJCAI, 2017)

Clustering-Based Relational Unsupervised Representation Learning with an Explicit Distributed Representation. - Sebastijan Dumancic; Hendrik Blockeel (IJCAI, 2017)

PU-learning Disjunctive Concepts in ILP. - Hendrik Blockeel (ILP (Late Breaking Papers), 2017)

Demystifying Relational Latent Representations. - Sebastijan Dumancic; Hendrik Blockeel (ILP, 2017)

Constraint-based clustering selection. - Toon van Craenendonck; Hendrik Blockeel (Mach. Learn., 2017)

An expressive dissimilarity measure for relational clustering using neighbourhood trees. - Sebastijan Dumancic; Hendrik Blockeel (Mach. Learn., 2017)

Bias Specification Language. - Hendrik Blockeel (Encyclopedia of Machine Learning and Data Mining, 2017)

Hypothesis Language. - Hendrik Blockeel (Encyclopedia of Machine Learning and Data Mining, 2017)

Hypothesis Space. - Hendrik Blockeel (Encyclopedia of Machine Learning and Data Mining, 2017)

Observation Language. - Hendrik Blockeel (Encyclopedia of Machine Learning and Data Mining, 2017)

Multi-Instance Learning. - Soumya Ray; Stephen Scott 001; Hendrik Blockeel (Encyclopedia of Machine Learning and Data Mining, 2017)

Multiple-Instance Learning. - Soumya Ray; Stephen Scott 001; Hendrik Blockeel (Encyclopedia of Machine Learning and Data Mining, 2017)

Relational Learning. - Jan Struyf; Hendrik Blockeel (Encyclopedia of Machine Learning and Data Mining, 2017)

MERCS: Multi-Directional Ensembles of Regression and Classification Trees. - Elia Van Wolputte; Evgeniya Korneva; Hendrik Blockeel (AAAI, 2018)

Model Selection for Multi-directional Ensemble of Regression and Classification Trees. - Evgeniya Korneva; Hendrik Blockeel (BNCAI, 2018)

COBRASTS: A New Approach to Semi-supervised Clustering of Time Series. - Toon van Craenendonck; Wannes Meert; Sebastijan Dumancic; Hendrik Blockeel (DS, 2018)

COBRAS: Interactive Clustering with Pairwise Queries. - Toon van Craenendonck; Sebastijan Dumancic; Elia Van Wolputte; Hendrik Blockeel (IDA, 2018)

Elements of an Automatic Data Scientist. - Luc De Raedt; Hendrik Blockeel; Samuel Kolb; Stefano Teso; Gust Verbruggen (IDA, 2018)

Interactive Time Series Clustering with COBRASTS. - Toon van Craenendonck; Wannes Meert; Sebastijan Dumancic; Hendrik Blockeel (ECML/PKDD (3), 2018)

COBRAS: Fast, Iterative, Active Clustering with Pairwise Constraints. - Toon van Craenendonck; Sebastijan Dumancic; Elia Van Wolputte; Hendrik Blockeel (CoRR, 2018)

COBRAS-TS: A new approach to Semi-Supervised Clustering of Time Series. - Toon van Craenendonck; Wannes Meert; Sebastijan Dumancic; Hendrik Blockeel (CoRR, 2018)

Declarative data analysis. - Hendrik Blockeel (Int. J. Data Sci. Anal., 2018)

A machine learning based framework to identify and classify long terminal repeat retrotransposons. - Leander Schietgat; Celine Vens; Ricardo Cerri; Carlos N. Fischer; Eduardo P. Costa; Jan Ramon; Claudia M. A. Carareto; Hendrik Blockeel (PLoS Comput. Biol., 2018)

Learning Relational Representations with Auto-encoding Logic Programs. - Sebastijan Dumancic; Tias Guns; Wannes Meert; Hendrik Blockeel (IJCAI, 2019)

LazyBum: Decision Tree Learning Using Lazy Propositionalization. - Jonas Schouterden; Jesse Davis; Hendrik Blockeel (ILP, 2019)

Multi-directional Rule Set Learning. - Jonas Schouterden; Jesse Davis; Hendrik Blockeel (DS, 2020)

Missing Value Imputation with MERCS: A Faster Alternative to MissForest. - Elia Van Wolputte; Hendrik Blockeel (DS, 2020)

Towards Better Evaluation of Multi-target Regression Models. - Evgeniya Korneva; Hendrik Blockeel (PKDD/ECML Workshops, 2020)

Tackling Noise in Active Semi-supervised Clustering. - Jonas Soenen; Sebastijan Dumancic; Toon van Craenendonck; Hendrik Blockeel (ECML/PKDD (2), 2020)

Feature Interactions in XGBoost. - Kshitij Goyal; Sebastijan Dumancic; Hendrik Blockeel (CoRR, 2020)

DTAIDistance. - Wannes Meert; Kilian Hendrickx; Toon van Craenendonck; Pieter Robberechts; Hendrik Blockeel; Jesse Davis (Zenodo, 2020)

Combining Predictions Under Uncertainty: The Case of Random Decision Trees. - Florian Busch; Moritz Kulessa; Eneldo Loza Mencía; Hendrik Blockeel (DS, 2021)

Unifying Knowledge Base Completion with PU Learning to Mitigate the Observation Bias. - Jonas Schouterden; Jessa Bekker; Jesse Davis; Hendrik Blockeel (AAAI, 2022)

Automatic Generation of Product Concepts from Positive Examples, with an Application to Music Streaming. - Kshitij Goyal; Wannes Meert; Hendrik Blockeel; Elia Van Wolputte; Koen Vanderstraeten; Wouter Pijpops; Kurt Jaspers (BNAIC/BENELEARN, 2022)

SaDe: Learning Models that Provably Satisfy Domain Constraints. - Kshitij Goyal; Sebastijan Dumancic; Hendrik Blockeel (ECML/PKDD (5), 2022)

Towards Neural Network Interpretability Using Commonsense Knowledge Graphs. - Youmna Ismaeil; Daria Stepanova 001; Trung-Kien Tran; Piyapat Saranrittichai; Csaba Domokos; Hendrik Blockeel (ISWC, 2022)

LinC: Explaining Time Series Clusterings with User-Provided Constraints. - Simiao Lin; Aras Yurtman; Jonas Soenen; Hendrik Blockeel (PKDD/ECML Workshops (3), 2023)

Estimating Dynamic Time Warping Distance Between Time Series with Missing Data. - Aras Yurtman; Jonas Soenen; Wannes Meert; Hendrik Blockeel (ECML/PKDD (5), 2023)

FeaBI: A Feature Selection-Based Framework for Interpreting KG Embeddings. - Youmna Ismaeil; Daria Stepanova 001; Trung-Kien Tran; Hendrik Blockeel (ISWC, 2023)

Look beyond the Surface: A Demo for Explaining Knowledge Graph Embeddings and Entity Similarity. - Huu Tan Mai; Youmna Ismaeil; Daria Stepanova 001; Trung-Kien Tran; Hendrik Blockeel (ISWC (Posters/Demos/Industry), 2023)

AD-MERCS: Modeling Normality and Abnormality in Unsupervised Anomaly Detection. - Jonas Soenen; Elia Van Wolputte; Vincent Vercruyssen; Wannes Meert; Hendrik Blockeel (CoRR, 2023)

A Scalable Ensemble Approach to Forecast the Electricity Consumption of Households. - Lola Botman; Jonas Soenen; Konstantinos Theodorakos; Aras Yurtman; Jessa Bekker; Koen Vanthournout; Hendrik Blockeel; Bart De Moor; Jesus Lago (IEEE Trans. Smart Grid, 2023)

Decision trees: from efficient prediction to responsible AI. - Hendrik Blockeel; Laurens Devos; Benoît Frénay; Géraldin Nanfack; Siegfried Nijssen (Frontiers Artif. Intell., 2023)

DeepSaDe: Learning Neural Networks That Guarantee Domain Constraint Satisfaction. - Kshitij Goyal; Sebastijan Dumancic; Hendrik Blockeel (AAAI, 2024)

Fast and interpretable electricity consumption scenario generation for individual consumers. - Jonas Soenen; Aras Yurtman; Thijs Becker; Koen Vanthournout; Hendrik Blockeel (CoRR, 2024)

Quantitative Evaluation of Motif Sets in Time Series. - Daan Van Wesenbeeck; Aras Yurtman; Wannes Meert; Hendrik Blockeel (CoRR, 2024)

LoCoMotif: discovering time-warped motifs in time series. - Daan Van Wesenbeeck; Aras Yurtman; Wannes Meert; Hendrik Blockeel (Data Min. Knowl. Discov., 2024)

Steering the LoCoMotif: Using Domain Knowledge in Time Series Motif Discovery. - Aras Yurtman; Daan Van Wesenbeeck; Wannes Meert; Hendrik Blockeel (CoRR, 2025)

Warping and Matching Subsequences Between Time Series. - Simiao Lin; Wannes Meert; Pieter Robberechts; Hendrik Blockeel (CoRR, 2025)