Siegfried Nijssen

ORCID

Publication Activity (10 Years)

Years Active: 2001-2024
Publications (10 Years): 51

Top Venues

CoRR

IDA

Publications

Valentin Lemaire, Gaël Aglin, Siegfried Nijssen
Interpretable Quantile Regression by Optimal Decision Trees. IDA (2) (2024)
John O. R. Aoga, Juhee Bae, Stefanija Veljanoska, Siegfried Nijssen, Pierre Schaus
Impact of Weather Factors on Migration Intention Using Machine Learning Algorithms. Oper. Res. Forum 5 (1) (2024)
Alexandre Dubray, Pierre Schaus, Siegfried Nijssen
Anytime Weighted Model Counting with Approximation Guarantees for Probabilistic Inference. CP (2024)
Harold Silvère Kiossou, Pierre Schaus, Siegfried Nijssen, Gaël Aglin
Efficient Lookahead Decision Trees. IDA (2) (2024)
Bastián Véjar, Gaël Aglin, Ali Irfan Mahmutogullari, Siegfried Nijssen, Pierre Schaus, Tias Guns
An Efficient Structured Perceptron for NP-Hard Combinatorial Optimization Problems. CPAIOR (2) (2024)
Hendrik Blockeel, Laurens Devos, Benoît Frénay, Géraldin Nanfack, Siegfried Nijssen
Decision trees: from efficient prediction to responsible AI. Frontiers Artif. Intell. 6 (2023)
Julien Liénard, Kim Mens, Siegfried Nijssen
Extracting Unit Tests from Patterns Mined in Student Code to Provide Improved Feedback in Autograders. SATToSE (2023)
Alexandre Dubray, Pierre Schaus, Siegfried Nijssen
Probabilistic Inference by Projected Weighted Model Counting on Horn Clauses. CP (2023)
Lucile Dierckx, Rosana Veroneze, Siegfried Nijssen
RL-Net: Interpretable Rule Learning with Neural Networks. PAKDD (1) (2023)
Nicolas Golenvaux, Xavier Gillard, Siegfried Nijssen, Pierre Schaus
Partitioning a Map into Homogeneous Contiguous Regions: A Branch-And-Bound Approach Using Decision Diagrams (Short Paper). CP (2023)
Lucile Dierckx, Rosana Veroneze, Siegfried Nijssen
RL-Net: Interpretable Rule Learning with Neural Networks. NeSy (2023)
Alexandre Dubray, Guillaume Derval, Siegfried Nijssen, Pierre Schaus
Optimal Decoding of Hidden Markov Models with Consistency Constraints. DS (2022)
Harold Silvère Kiossou, Pierre Schaus, Siegfried Nijssen, Vinasétan Ratheil Houndji
Time Constrained DL8.5 Using Limited Discrepancy Search. ECML/PKDD (5) (2022)
Siegfried Nijssen, Pierre Schaus
From Inductive Databases to DL8.5 (short paper). KDID (2022)
Lucile Dierckx, Mélanie Beauvois, Siegfried Nijssen
Detection and Multi-label Classification of Bats. IDA (2022)
Anna L. D. Latour, Behrouz Babaki, Daniël Fokkinga, Marie Anastacio, Holger H. Hoos, Siegfried Nijssen
Exact stochastic constraint optimisation with applications in network analysis. Artif. Intell. 304 (2022)
Gaël Aglin, Siegfried Nijssen, Pierre Schaus
Learning Optimal Decision Trees Under Memory Constraints. ECML/PKDD (5) (2022)
Alexandre Dubray, Siegfried Nijssen, Isabelle Thomas, Pierre Schaus
A Seriation Based Framework to Visualize Multiple Aspects of Road Transport from GPS Trajectories. ITSC (2021)
Kim Mens, Siegfried Nijssen, Hoang-Son Pham
The good, the bad, and the ugly: mining for patterns in student source code. EASEAI@ESEC/SIGSOFT FSE (2021)
Alex Mattenet, Ian Davidson, Siegfried Nijssen, Pierre Schaus
Generic Constraint-based Block Modeling using Constraint Programming. J. Artif. Intell. Res. 70 (2021)
Gaël Aglin, Siegfried Nijssen, Pierre Schaus
Assessing Optimal Forests of Decision Trees. ICTAI (2021)
Gauthier Van Vracem, Siegfried Nijssen
Iterated Matrix Reordering. ECML/PKDD (3) (2021)
Hélène Verhaeghe, Siegfried Nijssen, Gilles Pesant, Claude-Guy Quimper, Pierre Schaus
Learning Optimal Decision Trees using Constraint Programming (Extended Abstract). IJCAI (2020)
Alexandre Dubray, Guillaume Derval, Siegfried Nijssen, Pierre Schaus
Mining Constrained Regions of Interest: An Optimization Approach. DS (2020)
Alex Lucía Mattenet, Ian Davidson, Siegfried Nijssen, Pierre Schaus
Constraint Programming for an Efficient and Flexible Block Modeling Solver. AAAI (2020)
Harold Silvère Kiossou, Yannik Schenk, Frédéric Docquier, Vinasétan Ratheil Houndji, Siegfried Nijssen, Pierre Schaus
Using an interpretable Machine Learning approach to study the drivers of International Migration. CoRR (2020)
John O. R. Aoga, Juhee Bae, Stefanija Veljanoska, Siegfried Nijssen, Pierre Schaus
Impact of weather factors on migration intention using machine learning algorithms. CoRR (2020)
Gaël Aglin, Siegfried Nijssen, Pierre Schaus
PyDL8.5: a Library for Learning Optimal Decision Trees. IJCAI (2020)
Hélène Verhaeghe, Siegfried Nijssen, Gilles Pesant, Claude-Guy Quimper, Pierre Schaus
Learning optimal decision trees using constraint programming. Constraints An Int. J. 25 (3-4) (2020)
Gaël Aglin, Siegfried Nijssen, Pierre Schaus
Learning Optimal Decision Trees Using Caching Branch-and-Bound Search. AAAI (2020)
Marvin Meeng, Harm de Vries, Peter A. Flach, Siegfried Nijssen, Arno J. Knobbe
Uni- and multivariate probability density models for numeric subgroup discovery. Intell. Data Anal. 24 (6) (2020)
Alex Mattenet, Ian Davidson, Siegfried Nijssen, Pierre Schaus
Generic Constraint-Based Block Modeling Using Constraint Programming. CP (2019)
Hoang-Son Pham, Siegfried Nijssen, Kim Mens, Dario Di Nucci, Tim Molderez, Coen De Roover, Johan Fabry, Vadim Zaytsev
Mining Patterns in Source Code Using Tree Mining Algorithms. DS (2019)
Anna Louise D. Latour, Behrouz Babaki, Siegfried Nijssen
Stochastic Constraint Propagation for Mining Probabilistic Networks. IJCAI (2019)
Hélène Verhaeghe, Siegfried Nijssen, Gilles Pesant, Claude-Guy Quimper, Pierre Schaus
Learning Optimal Decision Trees Using Constraint Programming. BNAIC/BENELEARN (2019)
Dario Di Nucci, Hoang-Son Pham, Johan Fabry, Coen De Roover, Kim Mens, Tim Molderez, Siegfried Nijssen, Vadim Zaytsev
A Language-Parametric Modular Framework for Mining Idiomatic Code Patterns. SATToSE (2019)
Anna Louise D. Latour, Behrouz Babaki, Siegfried Nijssen
Stochastic Constraint Propagation for Mining Probabilistic Networks. BNAIC/BENELEARN (2019)
Alex Mattenet, Ian Davidson, Siegfried Nijssen, Pierre Schaus
Generic Constraint-Based Block Modeling Using Constraint Programming. BNAIC/BENELEARN (2019)
John O. R. Aoga, Siegfried Nijssen, Pierre Schaus
Modeling Pattern Set Mining Using Boolean Circuits. CP (2019)
Anna L. D. Latour, Behrouz Babaki, Siegfried Nijssen
Stochastic Constraint Optimization using Propagation on Ordered Binary Decision Diagrams. CoRR (2018)
Thomas Bollen, Guillaume Leurquin, Siegfried Nijssen
ConvoMap: Using Convolution to Order Boolean Data. IDA (2018)
John O. R. Aoga, Tias Guns, Siegfried Nijssen, Pierre Schaus
Finding Probabilistic Rule Lists using the Minimum Description Length Principle. DS (2018)
Ricardo Cachucho, Siegfried Nijssen, Arno J. Knobbe
Biclustering Multivariate Time Series. IDA (2017)
Christian Bessiere, Luc De Raedt, Tias Guns, Lars Kotthoff, Mirco Nanni, Siegfried Nijssen, Barry O'Sullivan, Anastasia Paparrizou, Dino Pedreschi, Helmut Simonis
The Inductive Constraint Programming Loop. IEEE Intell. Syst. 32 (5) (2017)
Tias Guns, Anton Dries, Siegfried Nijssen, Guido Tack, Luc De Raedt
MiningZinc: A declarative framework for constraint-based mining. Artif. Intell. 244 (2017)
Thanh Le Van, Siegfried Nijssen, Matthijs van Leeuwen, Luc De Raedt
Semiring Rank Matrix Factorization. IEEE Trans. Knowl. Data Eng. 29 (8) (2017)
Anna L. D. Latour, Behrouz Babaki, Anton Dries, Angelika Kimmig, Guy Van den Broeck, Siegfried Nijssen
Combining Stochastic Constraint Optimization and Probabilistic Programming - From Knowledge Compilation to Constraint Solving. CP (2017)
Florian Demesmaeker, Amine Ghrab, Siegfried Nijssen, Sabri Skhiri
Discovering interesting patterns in large graph cubes. IEEE BigData (2017)
Thanh Le Van, Matthijs van Leeuwen, Ana Carolina Fierro, Dries De Maeyer, Jimmy Van den Eynden, Lieven P. C. Verbeke, Luc De Raedt, Kathleen Marchal, Siegfried Nijssen
Simultaneous discovery of cancer subtypes and subtype features by molecular data integration. Bioinform. 32 (17) (2016)
Ricardo Cachucho, Kaihua Liu, Siegfried Nijssen, Arno J. Knobbe
Bipeline: A Web-Based Visualization Tool for Biclustering of Multivariate Time Series. ECML/PKDD (3) (2016)
Lambert Schomaker, Andreas Weber, Michiel Thijssen, Maarten Heerlien, Aske Plaat, Siegfried Nijssen, Fons J. Verbeek, Michael S. Lew, Eulalia Gasso Miracle, Katy Wolstencroft, Ernest Suyver, Bart Verheij, Marco A. Wiering, René Dekker, Joost N. Kok, Lissa Roberts, H. Jaap van den Herik
Making Sense of Illustrated Handwritten Archives. DH (2016)
Thanh Le Van, Matthijs van Leeuwen, Siegfried Nijssen, Luc De Raedt
Rank Matrix Factorisation. PAKDD (1) (2015)
Emin Aksehirli, Siegfried Nijssen, Matthijs van Leeuwen, Bart Goethals
Finding Subspace Clusters Using Ranked Neighborhoods. ICDM Workshops (2015)
Michael Mampaey, Siegfried Nijssen, Ad Feelders, Rob M. Konijn, Arno J. Knobbe
Efficient algorithms for finding optimal binary features in numeric and nominal labeled data. Knowl. Inf. Syst. 42 (2) (2015)
Christian Bessiere, Luc De Raedt, Tias Guns, Lars Kotthoff, Mirco Nanni, Siegfried Nijssen, Barry O'Sullivan, Anastasia Paparrizou, Dino Pedreschi, Helmut Simonis
The Inductive Constraint Programming Loop. CoRR (2015)
Behrouz Babaki, Tias Guns, Siegfried Nijssen, Luc De Raedt
Constraint-Based Querying for Bayesian Network Exploration. IDA (2015)
Ricardo Cachucho, Marvin Meeng, Ugo Vespier, Siegfried Nijssen, Arno J. Knobbe
Mining multivariate time series with mixed sampling rates. UbiComp (2014)
Behrouz Babaki, Tias Guns, Siegfried Nijssen
Constrained Clustering Using Column Generation. CPAIOR (2014)
Thanh Le Van, Matthijs van Leeuwen, Siegfried Nijssen, Ana Carolina Fierro, Kathleen Marchal, Luc De Raedt
Ranked Tiling. ECML/PKDD (2) (2014)
Luc De Raedt, Siegfried Nijssen, Barry O'Sullivan, Michèle Sebag
Constraints, Optimization and Data (Dagstuhl Seminar 14411). Dagstuhl Reports 4 (10) (2014)
Vladimir Dzyuba, Matthijs van Leeuwen, Siegfried Nijssen, Luc De Raedt
Interactive Learning of Pattern Rankings. Int. J. Artif. Intell. Tools 23 (6) (2014)
Vladimir Dzyuba, Matthijs van Leeuwen, Siegfried Nijssen, Luc De Raedt
Active Preference Learning for Ranking Patterns. ICTAI (2013)
Ugo Vespier, Siegfried Nijssen, Arno J. Knobbe
Mining characteristic multi-scale motifs in sensor-based time series. CIKM (2013)
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) (2013)
Tias Guns, Anton Dries, Guido Tack, Siegfried Nijssen, Luc De Raedt
The MiningZinc Framework for Constraint-Based Itemset Mining. ICDM Workshops (2013)
Sean Gilpin, Siegfried Nijssen, Ian N. Davidson
Formalizing Hierarchical Clustering as Integer Linear Programming. AAAI (2013)
Tias Guns, Anton Dries, Guido Tack, Siegfried Nijssen, Luc De Raedt
MiningZinc: A Modeling Language for Constraint-Based Mining. IJCAI (2013)
Tias Guns, Siegfried Nijssen, Luc De Raedt
k-Pattern Set Mining under Constraints. IEEE Trans. Knowl. Data Eng. 25 (2) (2013)
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) (2013)
Benjamin Négrevergne, Anton Dries, Tias Guns, Siegfried Nijssen
Dominance Programming for Itemset Mining. ICDM (2013)
Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezný
A Revised Publication Model for ECML PKDD CoRR (2012)
Ugo Vespier, Arno J. Knobbe, Siegfried Nijssen, Joaquin Vanschoren
MDL-Based Analysis of Time Series at Multiple Time-Scales. ECML/PKDD (2) (2012)
Anton Dries, Siegfried Nijssen
Mining Patterns in Networks using Homomorphism. SDM (2012)
Michael Mampaey, Siegfried Nijssen, Ad Feelders, Arno J. Knobbe
Efficient Algorithms for Finding Richer Subgroup Descriptions in Numeric and Nominal Data. ICDM (2012)
Thanh Le Van, Ana Carolina Fierro, Tias Guns, Matthijs van Leeuwen, Siegfried Nijssen, Luc De Raedt, Kathleen Marchal
Mining Local Staircase Patterns in Noisy Data. ICDM Workshops (2012)
Joris Renkens, Guy Van den Broeck, Siegfried Nijssen
k-Optimal: a novel approximate inference algorithm for ProbLog. Mach. Learn. 89 (3) (2012)
Björn Bringmann, Siegfried Nijssen, Albrecht Zimmermann
Pattern-Based Classification: A Unifying Perspective CoRR (2011)
Tias Guns, Siegfried Nijssen, Luc De Raedt
Evaluating Pattern Set Mining Strategies in a Constraint Programming Framework. PAKDD (2) (2011)
Siegfried Nijssen, Aída Jiménez, Tias Guns
Constraint-Based Pattern Mining in Multi-relational Databases. ICDM Workshops (2011)
Tias Guns, Siegfried Nijssen, Albrecht Zimmermann, Luc De Raedt
Declarative Heuristic Search for Pattern Set Mining. ICDM Workshops (2011)
Anton Dries, Siegfried Nijssen
Mining Patterns in Networks using Homomorphism CoRR (2011)
Tias Guns, Siegfried Nijssen, Luc De Raedt
Itemset mining: A constraint programming perspective. Artif. Intell. 175 (12-13) (2011)
Luc De Raedt, Siegfried Nijssen, Barry O'Sullivan, Pascal Van Hentenryck
Constraint Programming meets Machine Learning and Data Mining (Dagstuhl Seminar 11201). Dagstuhl Reports 1 (5) (2011)
Luc De Raedt, Siegfried Nijssen
Towards Programming Languages for Machine Learning and Data Mining (Extended Abstract). ISMIS (2011)
Joris Renkens, Guy Van den Broeck, Siegfried Nijssen
k-Optimal: A Novel Approximate Inference Algorithm for ProbLog. ILP (2011)
Siegfried Nijssen, Tias Guns
Integrating Constraint Programming and Itemset Mining. ECML/PKDD (2) (2010)
Anton Dries, Siegfried Nijssen
Analyzing graph databases by aggregate queries. MLG@KDD (2010)
Siegfried Nijssen, Élisa Fromont
Optimal constraint-based decision tree induction from itemset lattices. Data Min. Knowl. Discov. 21 (1) (2010)
Tias Guns, Hong Sun, Kathleen Marchal, Siegfried Nijssen
Cis-regulatory module detection using constraint programming. BIBM (2010)
Luc De Raedt, Tias Guns, Siegfried Nijssen
Constraint Programming for Data Mining and Machine Learning. AAAI (2010)
Anton Dries, Luc De Raedt, Siegfried Nijssen
Mining Predictive k-CNF Expressions. IEEE Trans. Knowl. Data Eng. 22 (5) (2010)
Siegfried Nijssen, Luc De Raedt
Grammar Mining. SDM (2009)
Siegfried Nijssen, Tias Guns, Luc De Raedt
Correlated itemset mining in ROC space: a constraint programming approach. KDD (2009)
Mathias Verbeke, Bettina Berendt, Siegfried Nijssen
Data Mining, Interactive Semantic Structuring, and Collaboration: A Diversity-aware Method for Sense-making in Search. LivingWeb@ISWC (2009)
Jan Ramon, Siegfried Nijssen
Polynomial-Delay Enumeration of Monotonic Graph Classes. J. Mach. Learn. Res. 10 (2009)
Anton Dries, Siegfried Nijssen, Luc De Raedt
A query language for analyzing networks. CIKM (2009)
Siegfried Nijssen
Bayes optimal classification for decision trees. ICML (2008)
Björn Bringmann, Siegfried Nijssen
What Is Frequent in a Single Graph?. PAKDD (2008)
Luc De Raedt, Tias Guns, Siegfried Nijssen
Constraint programming for itemset mining. KDD (2008)
Jan Ramon, Siegfried Nijssen
General Graph Refinement with Polynomial Delay. MLG (2007)

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Publication Activity (10 Years)

Top Topics

Top Venues

Siegfried Nijssen