Wouter Duivesteijn

According to our database, Wouter Duivesteijn authored at least 42 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Exceptional Subitizing Patterns: Exploring Mathematical Abilities of Finnish Primary School Children with Piecewise Linear Regression.

Rianne Margaretha Schouten, Wouter Duivesteijn, Pekka Räsänen, Jacob M. Paul, Mykola Pechenizkiy

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track, 2024

RMI-RRG: A Soft Protocol to Postulate Monotonicity Constraints for Tabular Datasets.

Iko Vloothuis, Wouter Duivesteijn

Proceedings of the Advances in Intelligent Data Analysis XXII, 2024

2022

Mining sequences with exceptional transition behaviour of varying order using quality measures based on information-theoretic scoring functions.

Rianne Margaretha Schouten, Marcos L. P. Bueno, Wouter Duivesteijn, Mykola Pechenizkiy

Data Min. Knowl. Discov., 2022

Exceptional Model Mining for Repeated Cross-Sectional Data (EMM-RCS).

Rianne Margaretha Schouten, Wouter Duivesteijn, Mykola Pechenizkiy

Proceedings of the 2022 SIAM International Conference on Data Mining, 2022

Efficient Subgroup Discovery Through Auto-Encoding.

Joost F. van der Haar, Sander C. Nagelkerken, Igor G. Smit, Kjell van Straaten, Janneke A. Tack, Rianne Margaretha Schouten, Wouter Duivesteijn

Proceedings of the Advances in Intelligent Data Analysis XX, 2022

A Clustering-Inspired Quality Measure for Exceptional Preferences Mining - Design Choices and Consequences.

Ruben Franciscus Adrianus Verhaegh, Jacco Johannes Egbert Kiezebrink, Frank Nusteling, Arnaud Wander André Rio, Márton Bendegúz Bendicsek, Wouter Duivesteijn, Rianne Margaretha Schouten

Proceedings of the Discovery Science - 25th International Conference, 2022

2021

Adversarial balancing-based representation learning for causal effect inference with observational data.

Xin Du, Lei Sun, Wouter Duivesteijn, Alexander G. Nikolaev, Mykola Pechenizkiy

Data Min. Knowl. Discov., 2021

Beyond Discriminant Patterns: On the Robustness of Decision Rule Ensembles.

Xin Du, Subramanian Ramamoorthy, Wouter Duivesteijn, Jin Tian, Mykola Pechenizkiy

CoRR, 2021

Exceptional Gestalt Mining: Combining Magic Cards to Make Complex Coalitions Thrive.

Wouter Duivesteijn, Thomas C. van Dijk

Proceedings of the Machine Learning and Data Mining for Sports Analytics, 2021

2020

How to cheat the page limit.

Wouter Duivesteijn, Sibylle Hess, Xin Du

WIREs Data Mining Knowl. Discov., 2020

Exceptional spatio-temporal behavior mining through Bayesian non-parametric modeling.

Xin Du, Yulong Pei, Wouter Duivesteijn, Mykola Pechenizkiy

Data Min. Knowl. Discov., 2020

Softmax-based Classification is k-means Clustering: Formal Proof, Consequences for Adversarial Attacks, and Improvement through Centroid Based Tailoring.

Sibylle Hess, Wouter Duivesteijn, Decebal Constantin Mocanu

CoRR, 2020

Exceptional in so Many Ways - Discovering Descriptors That Display Exceptional Behavior on Contrasting Scenarios.

José María Luna, Mykola Pechenizkiy, Wouter Duivesteijn, Sebastián Ventura

IEEE Access, 2020

Predicting Remaining Useful Life with Similarity-Based Priors.

Youri Soons, Remco M. Dijkman, Maurice Jilderda, Wouter Duivesteijn

Proceedings of the Advances in Intelligent Data Analysis XVIII, 2020

Fairness in Network Representation by Latent Structural Heterogeneity in Observational Data.

Xin Du, Yulong Pei, Wouter Duivesteijn, Mykola Pechenizkiy

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

k Is the Magic Number - Inferring the Number of Clusters Through Nonparametric Concentration Inequalities.

Sibylle Hess, Wouter Duivesteijn

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

DEvIANT: Discovering Significant Exceptional (Dis-)Agreement Within Groups.

Adnene Belfodil, Wouter Duivesteijn, Marc Plantevit, Sylvie Cazalens, Philippe Lamarre

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

The SpectACl of Nonconvex Clustering: A Spectral Approach to Density-Based Clustering.

Sibylle Hess, Wouter Duivesteijn, Philipp Honysz, Katharina Morik

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Discovering a taste for the unusual: exceptional models for preference mining.

Cláudio Rebelo de Sá, Wouter Duivesteijn, Paulo J. Azevedo, Alípio Mário Jorge, Carlos Soares, Arno J. Knobbe

Mach. Learn., 2018

Controversy Rules - Discovering Regions Where Classifiers (Dis-)Agree Exceptionally.

Oren Zeev-Ben-Mordehai, Wouter Duivesteijn, Mykola Pechenizkiy

CoRR, 2018

ICIE 1.0: A Novel Tool for Interactive Contextual Interaction Explanations.

Simon van der Zon, Wouter Duivesteijn, Werner van Ipenburg, Jan Veldsink, Mykola Pechenizkiy

Proceedings of the ECML PKDD 2018 Workshops, 2018

Subjectively Interesting Subgroup Discovery on Real-Valued Targets.

Jefrey Lijffijt, Bo Kang, Wouter Duivesteijn, Kai Puolamäki, Emilia Oikarinen, Tijl De Bie

Proceedings of the 34th IEEE International Conference on Data Engineering, 2018

ELBA: Exceptional Learning Behavior Analysis.

Xin Du, Wouter Duivesteijn, Mykola Pechenizkiy

Proceedings of the 11th International Conference on Educational Data Mining, 2018

2017

Exceptionally monotone models - the rank correlation model class for Exceptional Model Mining.

Lennart Downar, Wouter Duivesteijn

Knowl. Inf. Syst., 2017

BoostEMM - Transparent Boosting using Exceptional Model Mining.

Simon van der Zon, Oren Zeev-Ben-Mordehai, Tom Vrijdag, Werner van Ipenburg, Wouter Duivesteijn, Jan Veldsink, Mykola Pechenizkiy

Proceedings of the Second Workshop on MIning DAta for financial applicationS (MIDAS 2017) co-located with the 2017 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2017), 2017

Have It Both Ways - From A/B Testing to A&B Testing with Exceptional Model Mining.

Wouter Duivesteijn, Tara Farzami, Thijs Putman, Evertjan Peer, Hilde J. P. Weerts, Jasper N. Adegeest, Gerson Foks, Mykola Pechenizkiy

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

2016

Interpretable domain adaptation via optimization over the Stiefel manifold.

Christian Pölitz, Wouter Duivesteijn, Katharina Morik

Mach. Learn., 2016

Exceptional Model Mining - Supervised descriptive local pattern mining with complex target concepts.

Wouter Duivesteijn, Ad Feelders, Arno J. Knobbe

Data Min. Knowl. Discov., 2016

Exceptional Preferences Mining.

Cláudio Rebelo de Sá, Wouter Duivesteijn, Carlos Soares, Arno J. Knobbe

Proceedings of the Discovery Science - 19th International Conference, 2016

SCHEP - A Geometric Quality Measure for Regression Rule Sets, Gauging Ranking Consistency Throughout the Real-Valued Target Space.

Wouter Duivesteijn, Marvin Meeng

Proceedings of the Solving Large Scale Learning Tasks. Challenges and Algorithms, 2016

2015

Cost-based quality measures in subgroup discovery.

Rob M. Konijn, Wouter Duivesteijn, Marvin Meeng, Arno J. Knobbe

J. Intell. Inf. Syst., 2015

Understanding Where Your Classifier Does (Not) Work.

Wouter Duivesteijn, Julia Thaele

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

2014

ROCsearch - An ROC-guided Search Strategy for Subgroup Discovery.

Marvin Meeng, Wouter Duivesteijn, Arno J. Knobbe

Proceedings of the 2014 SIAM International Conference on Data Mining, 2014

RealKrimp - Finding Hyperintervals that Compress with MDL for Real-Valued Data.

Jouke Witteveen, Wouter Duivesteijn, Arno J. Knobbe, Peter Grünwald

Proceedings of the Advances in Intelligent Data Analysis XIII, 2014

Understanding Where Your Classifier Does (Not) Work - The SCaPE Model Class for EMM.

Wouter Duivesteijn, Julia Thaele

Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

2013

Discovering Local Subgroups, with an Application to Fraud Detection.

Rob M. Konijn, Wouter Duivesteijn, Wojtek Kowalczyk, Arno J. Knobbe

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2013

2012

Different slopes for different folks: mining for exceptional regression models with cook's distance.

Wouter Duivesteijn, Ad Feelders, Arno J. Knobbe

Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Multi-label LeGo - Enhancing Multi-label Classifiers with Local Patterns.

Wouter Duivesteijn, Eneldo Loza Mencía, Johannes Fürnkranz, Arno J. Knobbe

Proceedings of the Advances in Intelligent Data Analysis XI - 11th International Symposium, 2012

Multilayer Perceptron for Label Ranking.

Geraldina Ribeiro, Wouter Duivesteijn, Carlos Soares, Arno J. Knobbe

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2012, 2012

2011

Exploiting False Discoveries - Statistical Validation of Patterns and Quality Measures in Subgroup Discovery.

Wouter Duivesteijn, Arno J. Knobbe

Proceedings of the 11th IEEE International Conference on Data Mining, 2011

2010

Subgroup Discovery Meets Bayesian Networks -- An Exceptional Model Mining Approach.

Wouter Duivesteijn, Arno J. Knobbe, Ad Feelders, Matthijs van Leeuwen

Proceedings of the ICDM 2010, 2010

2008

Nearest Neighbour Classification with Monotonicity Constraints.

Wouter Duivesteijn, Ad Feelders

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2008