Wouter Duivesteijn

59 papers A* 9A 2B 10Journal 18Unranked 18
YearRankTypeTitle / Venue / Authors
2026 B conf
Exceptional Model Residual Mining, and Three Richer EMM Description Languages.
IDA
Aniket Mishra, Cristiana Carbunaru, Wouter Duivesteijn
2025 A* conf
Beyond Discriminant Patterns: On the Robustness of Decision Rule Ensembles.
ICDM
Xin Du, Subramanian Ramamoorthy, Wouter Duivesteijn, Jin Tian, Mykola Pechenizkiy
2025 — conf
Characterizing the Risk of Atrial Fibrillation in Cardiac Patients with Exceptional Electrocardiogram Phenotypes.
KDD (2)
Lieke van den Biggelaar, Rianne Margaretha Schouten, Ashley De Bie, R. Arthur Bouwman, Wouter Duivesteijn
2025 — conf
Conformalized Exceptional Model Mining: Telling Where Your Model Performs (Not) Well.
ECML/PKDD (3)
Xin Du, Sikun Yang, Wouter Duivesteijn, Mykola Pechenizkiy
2025 J jnl
Conformalized Exceptional Model Mining: Telling Where Your Model Performs (Not) Well.
CoRR
Xin Du, Sikun Yang, Wouter Duivesteijn, Mykola Pechenizkiy
2025 B conf
Local Subgroup Discovery on Attributed Network Graphs.
IDA
Carl Vico Heinrich, Tommie Lombarts, Jules Mallens, Luc Tortike, David Wolf, Wouter Duivesteijn
2025 — conf
World Cup of Flags: A Multi-relational Competitive Vexillology Dataset from Twitter.
Challenges and Algorithms for Knowledge Discovery from Data
Wouter Duivesteijn, Ad Feelders, Arno J. Knobbe
2024 — conf
Exceptional Subitizing Patterns: Exploring Mathematical Abilities of Finnish Primary School Children with Piecewise Linear Regression.
ECML/PKDD (10)
Rianne Margaretha Schouten, Wouter Duivesteijn, Pekka Räsänen, Jacob M. Paul, Mykola Pechenizkiy
2024 — conf
RMI-RRG: A Soft Protocol to Postulate Monotonicity Constraints for Tabular Datasets.
IDA (1)
Iko Vloothuis, Wouter Duivesteijn
2022 B conf
A Clustering-Inspired Quality Measure for Exceptional Preferences Mining - Design Choices and Consequences.
DS
Ruben Franciscus Adrianus Verhaegh, Jacco Johannes Egbert Kiezebrink, Frank Nusteling, Arnaud Wander André Rio, Márton Bendegúz Bendicsek, Wouter Duivesteijn, Rianne Margaretha Schouten
2022 B conf
Efficient Subgroup Discovery Through Auto-Encoding.
IDA
Joost F. van der Haar, Sander C. Nagelkerken, Igor G. Smit, Kjell van Straaten, Janneke A. Tack, Rianne Margaretha Schouten, Wouter Duivesteijn
2022 A conf
Exceptional Model Mining for Repeated Cross-Sectional Data (EMM-RCS).
SDM
Rianne Margaretha Schouten, Wouter Duivesteijn, Mykola Pechenizkiy
2022 J jnl
Mining sequences with exceptional transition behaviour of varying order using quality measures based on information-theoretic scoring functions.
Data Min. Knowl. Discov.
Rianne Margaretha Schouten, Marcos L. P. Bueno, Wouter Duivesteijn, Mykola Pechenizkiy
2021 J jnl
Adversarial balancing-based representation learning for causal effect inference with observational data.
Data Min. Knowl. Discov.
Xin Du, Lei Sun, Wouter Duivesteijn, Alexander G. Nikolaev, Mykola Pechenizkiy
2021 J jnl
Beyond Discriminant Patterns: On the Robustness of Decision Rule Ensembles.
CoRR
Xin Du, Subramanian Ramamoorthy, Wouter Duivesteijn, Jin Tian, Mykola Pechenizkiy
2021 — conf
Exceptional Gestalt Mining: Combining Magic Cards to Make Complex Coalitions Thrive.
MLSA@PKDD/ECML
Wouter Duivesteijn, Thomas C. van Dijk
2020 J jnl
Exceptional in so Many Ways - Discovering Descriptors That Display Exceptional Behavior on Contrasting Scenarios.
IEEE Access
José María Luna, Mykola Pechenizkiy, Wouter Duivesteijn, Sebastián Ventura
2020 J jnl
Exceptional spatio-temporal behavior mining through Bayesian non-parametric modeling.
Data Min. Knowl. Discov.
Xin Du, Yulong Pei, Wouter Duivesteijn, Mykola Pechenizkiy
2020 A* conf
Fairness in Network Representation by Latent Structural Heterogeneity in Observational Data.
AAAI
Xin Du, Yulong Pei, Wouter Duivesteijn, Mykola Pechenizkiy
2020 J jnl
How to cheat the page limit.
WIREs Data Mining Knowl. Discov.
Wouter Duivesteijn, Sibylle Hess, Xin Du
2020 B conf
Predicting Remaining Useful Life with Similarity-Based Priors.
IDA
Youri Soons, Remco M. Dijkman, Maurice Jilderda, Wouter Duivesteijn
2020 J jnl
Softmax-based Classification is k-means Clustering: Formal Proof, Consequences for Adversarial Attacks, and Improvement through Centroid Based Tailoring.
CoRR
Sibylle Hess, Wouter Duivesteijn, Decebal Constantin Mocanu
2019 J jnl
Adversarial Balancing-based Representation Learning for Causal Effect Inference with Observational Data.
CoRR
Xin Du, Lei Sun, Wouter Duivesteijn, Alexander G. Nikolaev, Mykola Pechenizkiy
2019 — ed.
Artificial Intelligence - 30th Benelux Conference, BNAIC 2018, 's-Hertogenbosch, The Netherlands, November 8-9, 2018, Revised Selected Papers
BNAIC
Martin Atzmueller, Wouter Duivesteijn
2019 — conf
DEvIANT: Discovering Significant Exceptional (Dis-)Agreement Within Groups.
ECML/PKDD (1)
Adnene Belfodil, Wouter Duivesteijn, Marc Plantevit, Sylvie Cazalens, Philippe Lamarre
2019 A* conf
The SpectACl of Nonconvex Clustering: A Spectral Approach to Density-Based Clustering.
AAAI
Sibylle Hess, Wouter Duivesteijn, Philipp Honysz, Katharina Morik
2019 J jnl
The SpectACl of Nonconvex Clustering: A Spectral Approach to Density-Based Clustering.
CoRR
Sibylle Hess, Wouter Duivesteijn, Philipp Honysz, Katharina Morik
2019 — conf
k Is the Magic Number - Inferring the Number of Clusters Through Nonparametric Concentration Inequalities.
ECML/PKDD (1)
Sibylle Hess, Wouter Duivesteijn
2019 J jnl
k is the Magic Number - Inferring the Number of Clusters Through Nonparametric Concentration Inequalities.
CoRR
Sibylle Hess, Wouter Duivesteijn
2018 B ed.
Advances in Intelligent Data Analysis XVII - 17th International Symposium, IDA 2018, 's-Hertogenbosch, The Netherlands, October 24-26, 2018, Proceedings
IDA
Wouter Duivesteijn, Arno Siebes, Antti Ukkonen
2018 J jnl
Controversy Rules - Discovering Regions Where Classifiers (Dis-)Agree Exceptionally.
CoRR
Oren Zeev-Ben-Mordehai, Wouter Duivesteijn, Mykola Pechenizkiy
2018 J jnl
Discovering a taste for the unusual: exceptional models for preference mining.
Mach. Learn.
Cláudio Rebelo de Sá, Wouter Duivesteijn, Paulo J. Azevedo, Alípio Mário Jorge, Carlos Soares, Arno J. Knobbe
2018 B conf
ELBA: Exceptional Learning Behavior Analysis.
EDM
Xin Du, Wouter Duivesteijn, Mykola Pechenizkiy
2018 — conf
ICIE 1.0: A Novel Tool for Interactive Contextual Interaction Explanations.
MIDAS/PAP@PKDD/ECML
Simon van der Zon, Wouter Duivesteijn, Werner van Ipenburg, Jan Veldsink, Mykola Pechenizkiy
2018 A* conf
Subjectively Interesting Subgroup Discovery on Real-Valued Targets.
ICDE
Jefrey Lijffijt, Bo Kang, Wouter Duivesteijn, Kai Puolamäki, Emilia Oikarinen, Tijl De Bie
2017 — conf
BoostEMM - Transparent Boosting using Exceptional Model Mining.
MIDAS@PKDD/ECML
Simon van der Zon, Oren Zeev-Ben-Mordehai, Tom Vrijdag, Werner van Ipenburg, Wouter Duivesteijn, Jan Veldsink, Mykola Pechenizkiy
2017 J jnl
Exceptionally monotone models - the rank correlation model class for Exceptional Model Mining.
Knowl. Inf. Syst.
Lennart Downar, Wouter Duivesteijn
2017 — conf
Have It Both Ways - From A/B Testing to A&B Testing with Exceptional Model Mining.
ECML/PKDD (3)
Wouter Duivesteijn, Tara Farzami, Thijs Putman, Evertjan Peer, Hilde J. P. Weerts, Jasper N. Adegeest, Gerson Foks, Mykola Pechenizkiy
2017 J jnl
Subjectively Interesting Subgroup Discovery on Real-valued Targets.
CoRR
Jefrey Lijffijt, Bo Kang, Wouter Duivesteijn, Kai Puolamäki, Emilia Oikarinen, Tijl De Bie
2016 J jnl
Exceptional Model Mining - Supervised descriptive local pattern mining with complex target concepts.
Data Min. Knowl. Discov.
Wouter Duivesteijn, Ad Feelders, Arno J. Knobbe
2016 B conf
Exceptional Preferences Mining.
DS
Cláudio Rebelo de Sá, Wouter Duivesteijn, Carlos Soares, Arno J. Knobbe
2016 J jnl
Interpretable domain adaptation via optimization over the Stiefel manifold.
Mach. Learn.
Christian Pölitz, Wouter Duivesteijn, Katharina Morik
2016 — conf
SCHEP - A Geometric Quality Measure for Regression Rule Sets, Gauging Ranking Consistency Throughout the Real-Valued Target Space.
Solving Large Scale Learning Tasks
Wouter Duivesteijn, Marvin Meeng
2015 J jnl
Cost-based quality measures in subgroup discovery.
J. Intell. Inf. Syst.
Rob M. Konijn, Wouter Duivesteijn, Marvin Meeng, Arno J. Knobbe
2015 A* conf
Exceptionally Monotone Models - The Rank Correlation Model Class for Exceptional Model Mining.
ICDM
Lennart Downar, Wouter Duivesteijn
2015 — conf
Understanding Where Your Classifier Does (Not) Work.
ECML/PKDD (3)
Wouter Duivesteijn, Julia Thaele
2014 — conf
ROCsearch - An ROC-Guided Search Strategy for Subgroup Discovery.
LWA
Marvin Meeng, Wouter Duivesteijn, Arno J. Knobbe
2014 A conf
ROCsearch - An ROC-guided Search Strategy for Subgroup Discovery.
SDM
Marvin Meeng, Wouter Duivesteijn, Arno J. Knobbe
2014 B conf
RealKrimp - Finding Hyperintervals that Compress with MDL for Real-Valued Data.
IDA
Jouke Witteveen, Wouter Duivesteijn, Arno J. Knobbe, Peter Grünwald
2014 A* conf
Understanding Where Your Classifier Does (Not) Work - The SCaPE Model Class for EMM.
ICDM
Wouter Duivesteijn, Julia Thaele
2013 — conf
Cost-Based Quality Measures in Subgroup Discovery.
PAKDD Workshops
Rob M. Konijn, Wouter Duivesteijn, Marvin Meeng, Arno J. Knobbe
2013 — conf
Discovering Local Subgroups, with an Application to Fraud Detection.
PAKDD (1)
Rob M. Konijn, Wouter Duivesteijn, Wojtek Kowalczyk, Arno J. Knobbe
2013 — —
Exceptional Model Mining.
Wouter Duivesteijn
2012 A* conf
Different slopes for different folks: mining for exceptional regression models with cook's distance.
KDD
Wouter Duivesteijn, Ad Feelders, Arno J. Knobbe
2012 B conf
Multi-label LeGo - Enhancing Multi-label Classifiers with Local Patterns.
IDA
Wouter Duivesteijn, Eneldo Loza Mencía, Johannes Fürnkranz, Arno J. Knobbe
2012 — conf
Multilayer Perceptron for Label Ranking.
ICANN (2)
Geraldina Ribeiro, Wouter Duivesteijn, Carlos Soares, Arno J. Knobbe
2011 A* conf
Exploiting False Discoveries - Statistical Validation of Patterns and Quality Measures in Subgroup Discovery.
ICDM
Wouter Duivesteijn, Arno J. Knobbe
2010 A* conf
Subgroup Discovery Meets Bayesian Networks -- An Exceptional Model Mining Approach.
ICDM
Wouter Duivesteijn, Arno J. Knobbe, Ad Feelders, Matthijs van Leeuwen
2008 — conf
Nearest Neighbour Classification with Monotonicity Constraints.
ECML/PKDD (1)
Wouter Duivesteijn, Ad Feelders