A. J. Feelders

According to our database, A. J. Feelders authored at least 62 papers between 1992 and 2023.

Collaborative distances:

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

2023

Explaining Model Behavior with Global Causal Analysis.

Marcel Robeer, Floris Bex, Ad Feelders, Henry Prakken

Proceedings of the Explainable Artificial Intelligence, 2023

2022

Adding Domain Knowledge to Improve Entity Resolution in 17th and 18th Century Amsterdam Archival Records.

Jurian Baas, Leon van Wissen, Jirsi Reinders, Mehdi M. Dastani, A. J. Feelders

Proceedings of the Towards a Knowledge-Aware AI - SEMANTiCS 2022, 2022

2021

Exploiting Transitivity Constraints for Entity Matching in Knowledge Graphs.

Jurian Baas, Mehdi Dastani, Ad Feelders

CoRR, 2021

Exploiting Transitivity for Entity Matching.

Jurian Baas, Mehdi Dastani, A. J. Feelders

Proceedings of the Semantic Web: ESWC 2021 Satellite Events, 2021

Generating Realistic Natural Language Counterfactuals.

Marcel Robeer, Floris Bex, Ad Feelders

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Entity Matching in Digital Humanities Knowledge Graphs.

Juriaan Baas, Mehdi M. Dastani, Ad Feelders

Proceedings of the Conference on Computational Humanities Research, 2021

Detection of Critical Events in Renewable Energy Production Time Series.

Laurens P. Stoop, Erik Duijm, Ad Feelders, Machteld van den Broek

Proceedings of the Advanced Analytics and Learning on Temporal Data, 2021

2020

Real-Time Outlier Detection in Time Series Data of Water Sensors.

Luuk van de Wiel, Daniel M. van Es, A. J. Feelders

Proceedings of the Advanced Analytics and Learning on Temporal Data, 2020

Tailored Graph Embeddings for Entity Alignment on Historical Data.

Jurian Baas, Mehdi Dastani, Ad Feelders

Proceedings of the iiWAS '20: The 22nd International Conference on Information Integration and Web-based Applications & Services, Virtual Event / Chiang Mai, Thailand, November 30, 2020

2019

Conditional Forecasting of Water Level Time Series with RNNs.

Bart J. van der Lugt, Ad Feelders

Proceedings of the Advanced Analytics and Learning on Temporal Data, 2019

2018

Data-driven fraud detection in international shipping.

Ron Triepels, Hennie Daniels, Ad Feelders

Expert Syst. Appl., 2018

2016

Learning from incomplete data in Bayesian networks with qualitative influences.

Andrés R. Masegosa, A. J. Feelders, Linda C. van der Gaag

Int. J. Approx. Reason., 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

Exploiting monotonicity constraints to reduce label noise: An experimental evaluation.

Ad Feelders, Tijmen Kolkman

Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

2015

Efficient algorithms for finding optimal binary features in numeric and nominal labeled data.

Michael Mampaey, Siegfried Nijssen, Ad Feelders, Rob M. Konijn, Arno J. Knobbe

Knowl. Inf. Syst., 2015

Exceptional Model Mining with Tree-Constrained Gradient Ascent.

Thomas E. Krak, Ad Feelders

Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

A Quantitative Comparison of Semantic Web Page Segmentation Approaches.

Robert Kreuzer, Jurriaan Hage, Ad Feelders

Proceedings of the Engineering the Web in the Big Data Era - 15th International Conference, 2015

Uncovering Document Fraud in Maritime Freight Transport Based on Probabilistic Classification.

Ron Triepels, Ad Feelders, Hennie A. M. Daniels

Proceedings of the Computer Information Systems and Industrial Management, 2015

2014

Exploiting Monotonicity Constraints in Active Learning for Ordinal Classification.

Pieter Soons, Ad Feelders

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

Real-Time Adaptive Residual Calculation for Detecting Trend Deviations in Systems with Natural Variability.

Steven P. D. Woudenberg, Linda C. van der Gaag, Ad Feelders, Armin R. W. Elbers

Proceedings of the Advances in Intelligent Data Analysis XIII, 2014

Real-time Adaptive Problem Detection in Poultry.

Steven P. D. Woudenberg, Linda C. van der Gaag, Ad Feelders, Armin R. W. Elbers

Proceedings of the ECAI 2014 - 21st European Conference on Artificial Intelligence, 18-22 August 2014, Prague, Czech Republic, 2014

2012

Active Learning with Monotonicity Constraints.

Nicola Barile, Ad Feelders

Proceedings of the Twelfth SIAM International Conference on Data Mining, 2012

Probability estimation and a competence model for rule based e-tutoring systems.

Diederik M. Roijers, Johan Jeuring, Ad Feelders

Proceedings of the Second International Conference on Learning Analytics and Knowledge, 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

Efficient Algorithms for Finding Richer Subgroup Descriptions in Numeric and Nominal Data.

Michael Mampaey, Siegfried Nijssen, Ad Feelders, Arno J. Knobbe

Proceedings of the 12th IEEE International Conference on Data Mining, 2012

2011

On Generating All Optimal Monotone Classifications.

Luite Stegeman, Ad Feelders

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

When Learning Naive Bayesian Classifiers Preserves Monotonicity.

Barbara F. I. Pieters, Linda C. van der Gaag, Ad Feelders

Proceedings of the Symbolic and Quantitative Approaches to Reasoning with Uncertainty, 2011

Monotone Instance Ranking with mira.

Nicola Barile, Ad Feelders

Proceedings of the Discovery Science - 14th International Conference, 2011

2010

Monotone Relabeling in Ordinal Classification.

Ad Feelders

Proceedings of the ICDM 2010, 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

2009

Aligning Bayesian Network Classifiers with Medical Contexts.

Linda C. van der Gaag, Silja Renooij, Ad Feelders, Arend de Groote, Marinus J. C. Eijkemans, Frank J. Broekmans, Bart C. J. M. Fauser

Proceedings of the Machine Learning and Data Mining in Pattern Recognition, 2009

Isotonic Classification Trees.

Rémon van de Kamp, Ad Feelders, Nicola Barile

Proceedings of the Advances in Intelligent Data Analysis VIII, 2009

2008

An Experimental Comparison of Different Inclusion Relations in Frequent Tree Mining.

Jeroen De Knijf, Ad Feelders

Fundam. Informaticae, 2008

Exceptional Model Mining.

Dennis Leman, Ad Feelders, Arno J. Knobbe

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

Nearest Neighbour Classification with Monotonicity Constraints.

Wouter Duivesteijn, Ad Feelders

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

Nonparametric Monotone Classification with MOCA.

Nicola Barile, Ad Feelders

Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

2007

A new parameter Learning Method for Bayesian Networks with Qualitative Influences.

Ad Feelders

Proceedings of the UAI 2007, 2007

Parameter Learning for Bayesian Networks with Strict Qualitative Influences.

A. J. Feelders, Robert van Straalen

Proceedings of the Advances in Intelligent Data Analysis VII, 2007

2006

Learning Bayesian network parameters under order constraints.

A. J. Feelders, Linda C. van der Gaag

Int. J. Approx. Reason., 2006

Discriminative Scoring of Bayesian Network Classifiers: a Comparative Study.

A. J. Feelders, Jevgenijs Ivanovs

Proceedings of the Third European Workshop on Probabilistic Graphical Models, 2006

2005

Confidence intervals for probabilistic network classifiers.

Michael Egmont-Petersen, A. J. Feelders, Bart Baesens

Comput. Stat. Data Anal., 2005

Learning Bayesian Network Parameters with Prior Knowledge about Context-Specific Qualitative Influences.

A. J. Feelders, Linda C. van der Gaag

Proceedings of the UAI '05, 2005

Bringing order into bayesian-network construction.

Eveline M. Helsper, Linda C. van der Gaag, A. J. Feelders, Willie Loeffen, Petra L. Geenen, Armin Elbers

Proceedings of the 3rd International Conference on Knowledge Capture (K-CAP 2005), 2005

Instability of Classifiers on Categorical Data.

Arno Siebes, Muhammad Subianto, A. J. Feelders

Proceedings of the 5th IEEE International Conference on Data Mining (ICDM 2005), 2005

Learning Bayesian Network Models from Incomplete Data using Importance Sampling.

Carsten Riggelsen, Ad Feelders

Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

2004

Monotonicity in Bayesian Networks.

Linda C. van der Gaag, Hans L. Bodlaender, A. J. Feelders

Proceedings of the UAI '04, 2004

2003

Pruning for Monotone Classification Trees.

A. J. Feelders, Martijn Pardoel

Proceedings of the Advances in Intelligent Data Analysis V, 2003

2002

Classification trees for problems with monotonicity constraints.

Rob Potharst, A. J. Feelders

SIGKDD Explor., 2002

2001

A general model for automated business diagnosis.

A. J. Feelders, Hennie A. M. Daniels

Eur. J. Oper. Res., 2001

MAMBO: Discovering Association Rules Based on Conditional Independencies.

Robert Castelo, A. J. Feelders, Arno Siebes

Proceedings of the Advances in Intelligent Data Analysis, 4th International Conference, 2001

2000

Methodological and practical aspects of data mining.

A. J. Feelders, Hennie A. M. Daniels, Marcel Holsheimer

Inf. Manag., 2000

Prior Knowledge in Economic Applications of Data Mining.

A. J. Feelders

Proceedings of the Principles of Data Mining and Knowledge Discovery, 2000

1999

Discussion on the paper by Friedman and Fisher.

A. J. Feelders

Stat. Comput., 1999

Credit scoring and reject inference with mixture models.

A. J. Feelders

Intell. Syst. Account. Finance Manag., 1999

Handling Missing Data in Trees: Surrogate Splits or Statistical Imputation.

A. J. Feelders

Proceedings of the Principles of Data Mining and Knowledge Discovery, 1999

1998

Bootstrapping and Validation of Metamodels in Simulation.

Jack P. C. Kleijnen, A. J. Feelders, Russell C. H. Cheng

Proceedings of the 30th conference on Winter simulation, 1998

Mining in the Presence of Selectivity Bias and its Application to Reject Inference.

A. J. Feelders, Soong Chang, Geoffrey J. McLachlan

Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining (KDD-98), 1998

1996

Learning from Biased Data Using Mixture Models.

A. J. Feelders

Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD-96), 1996

Data mining and related techniques.

A. J. Feelders

Proceedings of the EUROSIM'96, 1996

1995

Data Mining for Loan Evaluation at ABN AMRO: A Case Study.

A. J. Feelders, A. J. F. le Loux, J. W. van't Zand

Proceedings of the First International Conference on Knowledge Discovery and Data Mining (KDD-95), 1995

On the Statistical Comparison of Inductive Learning Methods.

A. J. Feelders, W. J. H. Verkooijen

Proceedings of the Learning from Data, 1995

1992

Explanation and diagnosis in business assessment.

Hennie A. M. Daniels, Ad Feelders

IEEE Trans. Syst. Man Cybern., 1992