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Research Output 2017 2019

2019
30 Downloads (Pure)

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

Du, X., Sun, L., Duivesteijn, W., Nikolaev, A. & Pechenizkiy, M., 30 Apr 2019, In : arXiv. 17 p., 1904.13335v1.

Research output: Contribution to journalArticleAcademic

Open Access
File
Education
Experiments
Deep learning
2 Downloads (Pure)

ICIE 1.0: a novel tool for interactive contextual interaction explanations

van der Zon, S. B., Duivesteijn, W., van Ipenburg, W., Veldsink, J. & Pechenizkiy, M., 1 Jan 2019, ECML PKDD 2018 Workshops - MIDAS 2018 and PAP 2018, Proceedings. Monreale, A. & Alzate, C. (eds.). Cham: Springer, p. 81-94 14 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11054 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Interaction
Banking
Insurance
Privacy
Transactions
9 Downloads (Pure)

The SpectACl of nonconvex clustering: a spectral approach to density-based clustering.

Hess, S., Duivesteijn, W., Honysz, P. & Morik, K., 2019, Proceedings of 33rd AAAI Conference on Artificial IntelligenceAAAI. Association for the Advancement of Artificial Intelligence, 27 p.

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

Open Access
File
Experiments
2018
1 Downloads (Pure)

30th Benelux conference on artificial intelligence: BNAIC 2018 preproceedings, November 8-9, 2018, 's-Hertogenbosch, The Netherlands

Atzmüller, M. (ed.) & Duivesteijn, W. (ed.), 2018, 344 p.

Research output: Book/ReportBook editingAcademicpeer-review

Advances in intelligent data analysis XVII: 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24–26, 2018, Proceedings

Duivesteijn, W. (ed.), Siebes, A. (ed.) & Ukkonen, A. (ed.), 2018, Berlin: Springer. (Lecture notes in computer science; vol. 11191)( Information Systems and Applications, incl. Internet/Web, and HCI; vol. 11191)

Research output: Book/ReportBook editingAcademicpeer-review

1 Citation (Scopus)
25 Downloads (Pure)

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

de Sá, C. R., Duivesteijn, W., Azevedo, P., Jorge, A. M., Soares, C. & Knobbe, A., 1 Nov 2018, In : Machine Learning. 107, 11, p. 1775-1807 33 p.

Research output: Contribution to journalArticleAcademicpeer-review

Open Access
File
Labels
Data mining
15 Downloads (Pure)

ELBA: Exceptional Learning Behavior Analysis

Du, X., Duivesteijn, W., Klabbers, M. D. & Pechenizkiy, M., 2018, Proceedings of the 11th International Conference on Educational Data Mining, EDM 2018. p. 312-318

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Open Access
File
Students

Preface

Duivesteijn, W., Siebes, A. & Ukkonen, A., 1 Jan 2018, Advances in Intelligent Data Analysis XVII: 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24–26, 2018, Proceedings. Duivesteijn, W., Siebes, A. & Ukkonen, A. (eds.). Berlin: Springer, p. V-VI 2 p. (Lecture Notes in Computer Science; vol. 11191).

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

1 Citation (Scopus)

Subjectively interesting subgroup discovery on real-valued targets

Lijffijt, J., Kang, B., Duivesteijn, W., Puolamäki, K., Oikarinen, E. & de Bie, T., 2018, Proceedings of the 34th IEEE International Conference on Data Engineering (ICDE 2018). Piscataway: Institute of Electrical and Electronics Engineers, p. 1352-1355 8509369

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Data mining
2017
2376 Downloads (Pure)
Open Access
File
8 Downloads (Pure)

BoostEMM : Transparent boosting using exceptional model mining

van der Zon, S. B., Zeev Ben Mordehay, O., Vrijdag, T. S., van Ipenburg, W., Veldsink, J., Duivesteijn, W. & Pechenizkiy, M., 2017, Proceedings of the Second Workshop on MIning DAta for financial applicationS (MIDAS 2017), 18 September 2017, Skopje, Macedonia . Bordino, I., Caldarelli, G., Fumarola, F., Gullo, F. & Squartini, T. (eds.). p. 5-16 12 p. (CEUR Workshop Proceedings; vol. 1941).

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Open Access
File
Adaptive boosting
Transparency
4 Citations (Scopus)

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

Downar, L. & Duivesteijn, W., 2017, In : Knowledge and Information Systems. 51, 2, p. 369-394

Research output: Contribution to journalArticleAcademicpeer-review

Computational complexity
1 Citation (Scopus)
1 Downloads (Pure)

Have it both ways : from A/B testing to A&B testing with exceptional model mining

Duivesteijn, W., Farzami, T., Putman, T., Peer, E., Weerts, H. J. P., Adegeest, J. N., Foks, G. & Pechenizkiy, M., 30 Dec 2017, Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2017, Proceedings. Ceci, M., Dzeroski, S., Malerba, D., Altun, Y., Das, K., Read, J., Zitnik, M., Stefanowski, J. & Mielikäinen, T. (eds.). Cham : Springer, p. 114-126 13 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10536 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Mining
Testing
Websites
Industry
Profitability
45 Downloads (Pure)

The nutcracker framework for ensemble interpretability

Zeev Ben Mordehay, O., Duivesteijn, W. & Pechenizkiy, M., Oct 2017.

Research output: Contribution to conferencePosterAcademic

Open Access
File
Interpretability
Ensemble
Estimator
Subgroup
Random Forest