Publications
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Publications by Type per year also see DBLP, Google Scholar, or Semantic Scholar

Journal Papers
2024
Coupette, C, Vreeken, J & Rieck, B All the World's a (Hyper)Graph: A Data Drama. Digital Scholarship in the Humanities vol.39(1), pp 74-96, Oxford Academic Press, 2024. (IF 0.8)
2022
Cueppers, J, Kalofolias, J & Vreeken, J Omen: Discovering Sequential Patterns with Reliable Prediction Delays. Knowledge and Information Systems vol.64(4), pp 1013-1045, Springer, 2022. (IF 2.822)project website
2021
Dutta, A, Vreeken, J, Ghiringhelli, L & Bereau, T Data-driven Equation for Drug-Membrane Permeability across Drugs and Membranes. Journal of Chemical Physics vol.24(154), AIP, 2021. (IF 2.991)
Schmidt, F, Marx, A, Baumgarten, N, Hebel, M, Wegner, M, Kaulich, M, Leisegang, M, Brandes, R, Göke, J, Vreeken, J & Schulz, MH Integrative Analysis of Epigenetics Data Identifies Gene-Specific Regulatory Elements. Nucleic Acids Research, Oxford University Press, 2021. (IF 16.97)
2020
Mandros, P, Boley, M & Vreeken, J Discovering Dependencies with Reliable Mutual Information. Knowledge and Information Systems vol.62, pp 4223-4253, Springer, 2020. (IF 2.936)project website
Sutton, C, Boley, M, Ghiringhelli, L, Rupp, M, Vreeken, J & Scheffler, M Identifying Domains of Applicability of Machine Learning Models for Materials Science. Nature Communications vol.11(4428), pp 1-9, Nature Research, 2020. (IF 12.12)
2019
Marx, A & Vreeken, J Telling Cause from Effect by Local and Global Regression. Knowledge and Information Systems vol.60(3), pp 1277-1305, IEEE, 2019. (IF 2.397)project website
2018
Budhathoki, K & Vreeken, J Origo: Causal Inference by Compression. Knowledge and Information Systems vol.56(2), pp 285-307, Springer, 2018. (IF 2.247)project website
List, M, Hornakova, A, Vreeken, J & Schulz, MH JAMI — Fast computation of Conditional Mutual Information for ceRNA network analysis. Bioinformatics vol.34(17), pp 3050-3051, Oxford University Press, 2018. (IF 7.307)
Wu, H, Ning, Y, Chakraborty, P, Vreeken, J, Tatti, N & Ramakrishnan, N Generating Realistic Synthetic Population Datasets. Transactions on Knowledge Discovery from Data vol.12(4), pp 1-45, ACM, 2018. (IF 1.68)
2017
Boley, M, Goldsmith, BR, Ghiringhelli, LM & Vreeken, J Identifying Consistent Statements about Numerical Data with Dispersion-Corrected Subgroup Discovery. Data Mining and Knowledge Discovery vol.31(5), pp 1391-1418, Springer, 2017. (IF 3.160) (ECML PKDD'17 Journal Track)
Fischer, AK, Vreeken, J & Klakow, D Beyond Pairwise Similarity: Quantifying and Characterizing Linguistic Similarity between Groups of Languages by MDL. Computación y Sistemas vol.21(4), 2017. (Special Issue for the 18th International Conference on Intelligent Text Processing and Computational Linguistics, CICLing'17)
Goldsmith, B, Boley, M, Vreeken, J, Scheffler, M & Ghiringhelli, L Uncovering Structure-Property Relationships of Materials by Subgroup Discovery. New Journal of Physics vol.19, IOP Publishing Ltd and Deutsche Physikalische Gesellschaft, 2017. (IF 3.57) (Included in the NJP Highlights of 2017)
2016
Athukorala, K, Glowacka, D, Jacucci, G, Oulasvirta, A & Vreeken, J Is Exploratory Search Different? A Comparison of Information Search Behavior for Exploratory and Lookup Tasks. Journal of the Association for Information Science and Technology (JASIST) vol.67(11), pp 2635-2651, Wiley, 2016. (IF 2.26)
2015
Koutra, D, Kang, U, Vreeken, J & Faloutsos, C Summarizing and Understanding Large Graphs. Statistical Analysis and Data Mining vol.8(3), pp 183-202, Wiley, 2015.project website
Zimek, A & Vreeken, J The Blind Men and the Elephant: About Meeting the Problem of Multiple Truths in Data from Clustering and Pattern Mining Perspectives. Machine Learning vol.98(1), pp 121-155, Springer, 2015. (IF 1.587)
2014
Miettinen, P & Vreeken, J mdl4bmf: Minimal Description Length for Boolean Matrix Factorization. Transactions on Knowledge Discovery from Data vol.8(4), pp 1-30, ACM, 2014. (IF 1.68)project website
Nguyen, H-V, Müller, E, Vreeken, J & Böhm, K Unsupervised Interaction-Preserving Discretization of Multivariate Data. Data Mining and Knowledge Discovery vol.28(5), pp 1366-1397, Springer, 2014. (IF 2.877) (ECML PKDD'14 Journal Track)
Prakash, BA, Vreeken, J & Faloutsos, C Efficiently Spotting the Starting Points of an Epidemic in a Large Graph. Knowledge and Information Systems vol.38(1), pp 35-59, Springer, 2014. (IF 2.225)project website
Webb, G & Vreeken, J Efficient Discovery of the Most Interesting Associations. Transactions on Knowledge Discovery from Data vol.8(3), pp 1-31, ACM, 2014. (IF 1.68)implementation
Wu, H, Vreeken, J, Tatti, N & Ramakrishnan, N Uncovering the Plot: Detecting Surprising Coalitions of Entities in Multi-Relational Schemas. Data Mining and Knowledge Discovery vol.28(5), pp 1398-1428, Springer, 2014. (IF 2.877) (ECML PKDD'14 Journal Track)project websiteslides
2013
Mampaey, M & Vreeken, J Summarizing Categorical Data by Clustering Attributes. Data Mining and Knowledge Discovery vol.26(1), pp 130-173, Springer, 2013. (IF 2.877)project website
2012
Mampaey, M, Vreeken, J & Tatti, N Summarizing Data Succinctly with the Most Informative Itemsets. Transactions on Knowledge Discovery from Data vol.6(4), pp 1-44, ACM, 2012. (IF 1.68)project website
Tatti, N & Vreeken, J Comparing Apples and Oranges – Measuring Differences between Exploratory Data Mining Results. Data Mining and Knowledge Discovery vol.25(2), pp 173-207, Springer, 2012. (IF 1.545) (ECMLPKDD'11 Special Issue)project websiteslidesvideo recording
2011
Remmerie, N, De Vijlder, T, Valkenborg, D, Laukens, K, Smets, K, Vreeken, J, Mertens, I, Carpentier, S, Panis, B, De Jaeger, G, Prinsen, E & Witters, E Unraveling Tobacco BY-2 Protein Complexes with BN PAGE/LC-MS/MS and Clustering Methods. Journal of Proteomics vol.74(8), pp 1201-1217, Elsevier, 2011. (IF 5.074)project website
Vreeken, J, van Leeuwen, M & Siebes, A Krimp: Mining Itemsets that Compress. Data Mining and Knowledge Discovery vol.23(1), pp 169-214, Springer, 2011. (IF 2.950)project website
2010
Vreeken, J Making Pattern Mining Useful. ACM SIGKDD Explorations vol.12(1), pp 75-76, ACM Press, 2010.
Vreeken, J, Tatti, N & Goethals, B Useful Patterns (UP'10) ACM SIGKDD Workshop Report. ACM SIGKDD Explorations vol.12(2), pp 56-58, ACM Press, 2010.
2009
van Leeuwen, M, Vreeken, J & Siebes, A Identifying the Components. Data Mining and Knowledge Discovery vol.19(2), pp 176-193, Springer, 2009. (IF 2.950) (ECMLPKDD'09 Special Issue) (Best Student Paper)project websitevideo recording
Conference Papers
2024
Cueppers, J, Krieger, P & Vreeken, J Discovering Sequential Patterns with Predictable Inter-Event Delays. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), AAAI, 2024. (23.8% acceptance rate)project website
Mameche, S, Vreeken, J & Kaltenpoth, D Identifying Confounding from Causal Mechanism Shifts. In: Proceedings of the 27th International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR, 2024. (27.6% acceptance rate)project website
Mian, O, Mameche, S & Vreeken, J Learning Causal Networks from Episodic Data. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), ACM, 2024. (20% acceptance rate)project website
Schuster, MB, Wiegand, B & Vreeken, J Data is Moody: Discovering Data Modification Rules from Process Event Logs. In: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Data (ECMLPKDD), Springer, 2024. (24.0% acceptance rate)project website
Walter, N, Fischer, J & Vreeken, J Finding Interpretable Class-Specific Patterns through Efficient Neural Search. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), AAAI, 2024. (23.8% acceptance rate)project website
Wiegand, B, Klakow, D & Vreeken, J What are the Rules? Discovering Constraints from Data. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), AAAI, 2024. (oral presentation, 2,3% acceptance rate; 23.8% overall)project website
Xu, S, Walter, N, Kalofolias, J & Vreeken, J Learning Exceptional Subgroups by End-to-End Maximizing KL-divergence. In: Proceedings of the International Conference on Machine Learning (ICML), PMLR, 2024. (27.5% acceptance rate)project website
2023
Cueppers, J & Vreeken, J Below the Surface: Summarizing Event Sequences with Generalized Sequential Patterns. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), ACM, 2023. (22.1% acceptance rate)project website
Kaltenpoth, D & Vreeken, J Causal Discovery with Hidden Confounders using the Algorithmic Markov Condition. In: Proceedings of the International Conference on Uncertainty in Artificial Intelligence (UAI), AUAI, 2023. (31.2% acceptance rate)project website
Kaltenpoth, D & Vreeken, J Nonlinear Causal Discovery with Latent Confounders. In: Proceedings of the International Conference on Machine Learning (ICML), PMLR, 2023. (27.9% acceptance rate)project website
Kaltenpoth, D & Vreeken, J Identifying Selection Bias from Observational Data. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), pp 8177-8185, AAAI, 2023. (oral presentation, 10.8% acceptance rate; 19.6% overall)project website
Kamp, M, Fischer, J & Vreeken, J Federated Learning from Small Datasets. In: Proceedings of the International Conference on Representation Learning (ICLR), OpenReview, 2023. (31.8% acceptance rate)project website
Mameche, S, Kaltenpoth, D & Vreeken, J Learning Causal Models under Independent Changes. In: Proceedings of Neural Information Processing Systems (NeurIPS), PMRL, 2023. (26.1% acceptance rate)project website
Mian, O, Kaltenpoth, D, Kamp, M & Vreeken, J Nothing but Regrets — Privacy-Preserving Federated Causal Discovery. In: Proceedings of the 26nd International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR, 2023. (29% acceptance rate)project website
Mian, O, Kamp, M & Vreeken, J Information-Theoretic Causal Discovery and Intervention Detection over Multiple Environments. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), pp 9171-9179, AAAI, 2023. (19.6% acceptance rate)project website
Shani, C, Vreeken, J & Shahaf, D Towards Concept-Aware Large Language Models. In: Findings of the Association for Computational Linguistics (EMNLP Findings), ACL, 2023.
Wiegand, B, Klakow, D & Vreeken, J Why Are We Waiting? Discovering Interpretable Models for Predicting Sojourn and Waiting Times. In: SIAM International Conference on Data Mining (SDM), SIAM, 2023. (27.4% acceptance rate)project website
2022
Coupette, C, Dalleiger, S & Vreeken, J Differentially Describing Groups of Graphs. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), AAAI, 2022. (oral presentation 5.5% acceptance rate; overall 15.0%)project website
Dalleiger, S & Vreeken, J Efficiently Factorizing Boolean Matrices using Proximal Gradient Descent. In: Proceedings of Neural Information Processing Systems (NeurIPS), PMLR, 2022. (25.7% acceptance rate)project website
Dalleiger, S & Vreeken, J Discovering Significant Patterns under Sequential False Discovery Control. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp 263-272, ACM, 2022. (15.0% acceptance rate)project website
Hedderich, M, Fischer, J, Klakow, D & Vreeken, J Label-Descriptive Patterns and their Application to Characterizing Classification Errors. In: Proceedings of the International Conference on Machine Learning (ICML), PMLR, 2022. (21.9% acceptance rate)project website
Kalofolias, J & Vreeken, J Naming the most anomalous cluster in Hilbert Space for structures with attribute information. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), AAAI, 2022. (15.0% acceptance rate)project website
Mameche, S, Kaltenpoth, D & Vreeken, J Discovering Invariant and Changing Mechanisms from Data. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp 1242-1252, ACM, 2022. (15.0% acceptance rate)
Wiegand, B, Klakow, D & Vreeken, J Mining Interpretable Data-to-Sequence Generators. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), AAAI, 2022. (15.0% acceptance rate)project website
Xu, S, Mian, O, Marx, A & Vreeken, J Inferring Cause and Effect in the Presence of Heteroscedastic Noise. In: Proceedings of the International Conference on Machine Learning (ICML), PMLR, 2022. (21.9% acceptance rate)project website
2021
Budhathoki, K, Boley, M & Vreeken, J Discovering Reliable Causal Rules. In: Proceedings of the SIAM International Conference on Data Mining (SDM), SIAM, 2021. (21.2% acceptance rate)project website
Coupette, C & Vreeken, J Graph Similarity Description: How Are These Graphs Similar?. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp 185-195, ACM, 2021. (15.4% acceptance rate)
Fischer, J, Oláh, A & Vreeken, J What's in the Box? Explaining Neural Networks with Robust Rules. In: Proceedings of the International Conference on Machine Learning (ICML), PMLR, 2021. (21.4% acceptance rate)project website
Fischer, J & Vreeken, J Differentiable Pattern Set Mining. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp 383-392, ACM, 2021. (15.4% acceptance rate)
Kalofolias, J, Welke, P & Vreeken, J SUSAN: The Structural Similarity Random Walk Kernel. In: Proceedings of the SIAM International Conference on Data Mining (SDM), SIAM, 2021. (21.2% acceptance rate)project website
Mian, OA, Marx, A & Vreeken, J Discovering Fully Oriented Causal Networks. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), AAAI, 2021. (21.3% acceptance)project website
Wiegand, B, Klakow, D & Vreeken, J Mining Easily Understandable Models from Complex Event Data. In: SIAM International Conference on Data Mining (SDM), SIAM, 2021. (21.2% acceptance rate)project website
2020
Belth, C, Zheng, X, Vreeken, J & Koutra, D What is Normal, What is Strange, and What is Missing in a Knowledge Graph. In: Proceedings of the Web Conference (WWW), ACM, 2020. (oral presentation; overall acceptance rate 19.2%)
Cueppers, J & Vreeken, J Just Wait For It... Mining Sequential Patterns with Reliable Prediction Delays. In: Proceedings of the IEEE International Conference on Data Mining (ICDM'20), IEEE, 2020. (full paper, 9.8% acceptance rate; overall 19.7%) (invited for the KAIS Special Issue on the Best of IEEE ICDM 2020)project website
Dalleiger, S & Vreeken, J The Relaxed Maximum Entropy Distribution and its Application to Pattern Discovery. In: Proceedings of the IEEE International Conference on Data Mining (ICDM'20), IEEE, 2020. (19.7% acceptance rate)project website
Dalleiger, S & Vreeken, J Explainable Data Decompositions. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI'20), AAAI, 2020. (oral presentation 4.5% acceptance rate; overall 20.6%)project website
Fischer, J & Vreeken, J Discovering Succinct Pattern Sets Expressing Co-Occurrence and Mutual Exclusivity . In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), ACM, 2020. (16.8% acceptance rate)project website
Mandros, P, Kaltenpoth, D, Boley, M & Vreeken, J Discovering Functional Dependencies from Mixed-Type Data. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), ACM, 2020. (16.8% acceptance rate)project website
Penerath, F, Mandros, P & Vreeken, J Discovering Approximate Functional Dependencies using Smoothed Mutual Information . In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), ACM, 2020. (16.8% acceptance rate)
Zhang, Y, Humbert, M, Surma, B, Manoharan, P, Vreeken, J & Backes, M Towards Plausible Graph Anonymization. In: Proceedings of the Network and Distributed System Security Symposium (NDSS), The Internet Society, 2020. (17.4% acceptance rate)
2019
Fischer, J & Vreeken, J Sets of Robust Rules, and How to Find Them. In: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Data (ECMLPKDD), Springer, 2019. (17.7% acceptance rate)project website
Kalofolias, J, Boley, M & Vreeken, J Discovering Robustly Connected Subgraphs with Simple Descriptions. In: Proceedings of the IEEE International Conference on Data Mining (ICDM), IEEE, 2019. (18.5% acceptance rate)project website
Kaltenpoth, D & Vreeken, J We Are Not Your Real Parents: Telling Causal From Confounded by MDL. In: SIAM International Conference on Data Mining (SDM), SIAM, 2019. (22.9% acceptance rate)project website
Mandros, P, Boley, M & Vreeken, J Discovering Reliable Correlations in Categorical Data. In: Proceedings of the IEEE International Conference on Data Mining (ICDM'19), IEEE, 2019. (18.5% acceptance rate)project website
Mandros, P, Boley, M & Vreeken, J Discovering Reliable Dependencies from Data: Hardness and Improved Algorithms (Extended Abstract). In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), IJCAI, 2019. (Invited contribution to the IJCAI Sister Conference Best Paper Track)project website
Marx, A & Vreeken, J Identifiability of Cause and Effect using Regularized Regression. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), ACM, 2019. (oral presentation 9.2% acceptance rate; overall 14.2%)project website
Marx, A & Vreeken, J Testing Conditional Independence on Discrete Data using Stochastic Complexity. In: Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR, 2019. (31% acceptance rate)project website
2018
Budhathoki, K & Vreeken, J Accurate Causal Inference on Discrete Data. In: Proceedings of the IEEE International Conference on Data Mining (ICDM'18), IEEE, 2018. (19.9% acceptance rate)project website
Budhathoki, K & Vreeken, J Causal Inference on Event Sequences. In: Proceedings of the SIAM Conference on Data Mining (SDM), pp 55-63, SIAM, 2018. (23.2% acceptance rate)project website
Mandros, P, Boley, M & Vreeken, J Discovering Reliable Dependencies from Data: Hardness and Improved Algorithms. In: Proceedings of the IEEE International Conference on Data Mining (ICDM'18), IEEE, 2018. (full paper, 8.9% acceptance rate; overall 19.9%) (Best Paper Award)project website
Marx, A & Vreeken, J Causal Inference on Multivariate and Mixed Type Data. In: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Data (ECMLPKDD), Springer, 2018. (25% acceptance rate)project website
2017
Bertens, R, Vreeken, J & Siebes, A Efficiently Discovering Unexpected Pattern-Co-Occurrences. In: Proceedings of the SIAM International Conference on Data Mining (SDM), pp 126-134, SIAM, 2017. (25% acceptance rate)project websiteslides
Bhattacharyya, A & Vreeken, J Efficiently Summarising Event Sequences with Rich Interleaving Patterns. In: Proceedings of the SIAM Conference on Data Mining (SDM), pp 795-803, SIAM, 2017. (selected in the top 10 papers of SDM'17, 2.7% acceptance rate; overall 25%)project website
Budhathoki, K & Vreeken, J MDL for Causal Inference on Discrete Data. In: Proceedings of the IEEE International Conference on Data Mining (ICDM'17), pp 751-756, IEEE, 2017. (19.9% acceptance rate)project website
Budhathoki, K & Vreeken, J Correlation by Compression. In: Proceedings of the SIAM Conference on Data Mining (SDM), SIAM, 2017. (25% acceptance rate)project website
Kalofolias, J, Boley, M & Vreeken, J Efficiently Discovering Locally Exceptional yet Globally Representative Subgroups. In: Proceedings of the IEEE International Conference on Data Mining (ICDM'17), IEEE, 2017. (full paper, 9.3% acceptance rate; overall 19.9%)project website
Mandros, P, Boley, M & Vreeken, J Discovering Reliable Approximate Functional Dependencies. In: Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), pp 355-363, ACM, 2017. (oral presentation, 8.6% acceptance rate; overall 17.5%)project website
Marx, A & Vreeken, J Telling Cause from Effect by MDL-based Local and Global Regression. In: Proceedings of the IEEE International Conference on Data Mining (ICDM'17), pp 307-316, IEEE, 2017. (full paper, 9.3% acceptance rate; overall 19.9%) (invited for the KAIS Special Issue on the Best of IEEE ICDM 2017)project website
Pienta, R, Kahng, M, Lin, Z, Vreeken, J, Talukdar, P, Abello, J, Parameswaran, G & Chau, DH Adaptive Local Exploration of Large Graphs. In: Proceedings of the SIAM International Conference on Data Mining (SDM), pp 597-605, SIAM, 2017. (25% acceptance rate)project website
2016
Bertens, R, Vreeken, J & Siebes, A Keeping it Short and Simple: Summarising Complex Event Sequences with Multivariate Patterns. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'16), pp 735-744, ACM, 2016. (oral presentation, 8.9% acceptance rate; overall 18.1%)project websitevideo recording
Budhathoki, K & Vreeken, J Causal Inference by Compression. In: Proceedings of the IEEE International Conference on Data Mining (ICDM'16), IEEE, 2016. (full paper, 8.5% acceptance rate; overall 19.6%) (invited for the KAIS Special Issue on the Best of IEEE ICDM 2016)
Nguyen, H-V, Mandros, P & Vreeken, J Universal Dependency Analysis. In: Proceedings of the SIAM International Conference on Data Mining (SDM), pp 792-800, SIAM, 2016. (overall 25% acceptance rate)project websiteslides
Nguyen, H-V & Vreeken, J Flexibly Mining Better Subgroups. In: Proceedings of the SIAM International Conference on Data Mining (SDM), pp 585-593, SIAM, 2016. (overall 25% acceptance rate)project websiteslides
Nguyen, H-V & Vreeken, J Linear-time Detection of Non-Linear Changes in Massively High Dimensional Time Series. In: Proceedings of the SIAM International Conference on Data Mining (SDM), pp 828-836, SIAM, 2016. (overall 25% acceptance rate)project websiteslides
Rozenshtein, P, Gionis, A, Prakash, BA & Vreeken, J Reconstructing an Epidemic over Time. In: Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), pp 1835-1844, ACM, 2016. (18.1% acceptance rate)project website
2015
Budhathoki, K & Vreeken, J The Difference and the Norm – Characterising Similarities and Differences between Databases. In: Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), pp 206-223, Springer, 2015.project websiteslides
Karaev, S, Miettinen, P & Vreeken, J Getting to Know the Unknown Unknowns: Destructive-Noise Resistant Boolean Matrix Factorization. In: Proceedings of the SIAM International Conference on Data Mining (SDM), pp 325-333, SIAM, 2015.
Nguyen, H-V & Vreeken, J Non-Parametric Jensen-Shannon Divergence. In: Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), pp 173-189, Springer, 2015.project website
Pienta, R, Lin, Z, Kahng, M, Vreeken, J, Talukdar, PP, Abello, J, Parameswaran, G & Chau, DH AdaptiveNav: Adaptive Discovery of Interesting and Surprising Nodes in Large Graphs. In: Proceedings of the IEEE Conference on Visualization (VIS), IEEE, 2015.project websitevideo recording
Sundareisan, S, Vreeken, J & Prakash, BA Hidden Hazards: Finding Missing Nodes in Large Graph Epidemics. In: Proceedings of the SIAM International Conference on Data Mining (SDM), pp 415-423, SIAM, 2015.project website
Vreeken, J Causal Inference by Direction of Information. In: Proceedings of the SIAM International Conference on Data Mining (SDM), pp 909-917, SIAM, 2015.project website
2014
Athukorala, K, Oulasvirta, A, Glowacka, D, Vreeken, J & Jaccuci, G Narrow or Broad? Estimating Subjective Specificity in Exploratory Search. In: Proceedings of ACM Conference on Information and Knowledge Management (CIKM), pp 819-828, ACM, 2014. (IR track full paper, overall 21% acceptance rate)
Koutra, D, Kang, U, Vreeken, J & Faloutsos, C VoG: Summarizing and Understanding Large Graphs. In: Proceedings of the SIAM International Conference on Data Mining (SDM), pp 91-99, SIAM, 2014. (fast track journal invitation, as one of the best of SDM'14; full paper with presentation, 15.4% acceptance rate)project websiteslides
Kuzey, E, Vreeken, J & Weikum, G A Fresh Look on Knowledge Bases: Distilling Named Events from News. In: Proceedings of ACM Conference on Information and Knowledge Management (CIKM), pp 1689-1698, ACM, 2014. (KM track full paper, overall 21% acceptance rate)
Nguyen, H-V, Müller, E, Vreeken, J & Böhm, K Multivariate Maximal Correlation Analysis. In: Proceedings of the International Conference on Machine Learning (ICML), pp 775-783, JMLR: W&CP vol.32, 2014. (25.0% acceptance rate)project websiteslides
2013
Akoglu, L, Vreeken, J, Tong, H, Chau, DH, Tatti, N & Faloutsos, C Mining Connection Pathways for Marked Nodes in Large Graphs. In: Proceedings of the SIAM International Conference on Data Mining (SDM), pp 37-45, SIAM, 2013. (oral presentation, 14.4% acceptance rate; overal 25%)project website
Akşehirli, E, Goethals, B, Müller, E & Vreeken, J Cartification: A Neighborhood Preserving Transformation for Mining High Dimensional Data. In: Proceedings of the IEEE International Conference on Data Mining (ICDM), pp 937-942, IEEE, 2013. (19.6% acceptance rate)
Kontonasios, K-N, Vreeken, J & De Bie, T Maximum Entropy Models for Iteratively Identifying Subjectively Interesting Structure in Real-Valued Data. In: Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), pp 256-271, Springer, 2013.project websiteslides
Nguyen, H-V, Müller, E, Vreeken, J, Keller, F & Böhm, K CMI: An Information-Theoretic Contrast Measure for Enhancing Subspace Cluster and Outlier Detection. In: Proceedings of the SIAM International Conference on Data Mining (SDM), pp 198-206, SIAM, 2013. (oral presentation, 14.4% acceptance rate; overal 25%)project websiteslides
Ramon, J, Miettinen, P & Vreeken, J Detecting Bicliques in GF[q]. In: Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), pp 509-524, Springer, 2013.project website
2012
Akoglu, L, Tong, H, Vreeken, J & Faloutsos, C Fast and Reliable Anomaly Detection in Categoric Data. In: Proceedings of ACM Conference on Information and Knowledge Management (CIKM), pp 415-424, ACM, 2012. (full paper, 13.4% acceptance rate; 27% overall)project website
Prakash, BA, Vreeken, J & Faloutsos, C Spotting Culprits in Epidemics: How many and Which ones?. In: Proceedings of the IEEE International Conference on Data Mining (ICDM), pp 11-20, IEEE, 2012. (full paper, 10.7% acceptance rate; overall 20%)project websiteslides
Smets, K & Vreeken, J Slim: Directly Mining Descriptive Patterns. In: Proceedings of the SIAM International Conference on Data Mining (SDM), pp 236-247, SIAM, 2012. (oral presentation, 14.6% acceptance rate)project websiteslides
Tatti, N & Vreeken, J Discovering Descriptive Tile Trees by Fast Mining of Optimal Geometric Subtiles. In: Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), pp 9-24, Springer, 2012.project websiteslides
Tatti, N & Vreeken, J The Long and the Short of It: Summarising Event Sequences with Serial Episodes. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp 462-470, ACM, 2012. (17.6% acceptance rate)project websiteslidesvideo recording
2011
Kontonasios, K-N, Vreeken, J & De Bie, T Maximum Entropy Modelling for Assessing Results on Real-Valued Data. In: Proceedings of the IEEE International Conference on Data Mining (ICDM), pp 350-359, IEEE, 2011. (oral presentation, 12.3% acceptance rate; overall 18%)project website
Mampaey, M, Tatti, N & Vreeken, J Data Summarization with Informative Itemsets. In: Proceedings of the 23rd Benelux Conference on Artificial Intelligence (BNAIC), ISSN 1568-7805, 2011. (extended abstract of our KDD'11 paper)project website
Mampaey, M, Tatti, N & Vreeken, J Tell Me What I Need To Know: Succinctly Summarizing Data with Itemsets. In: Proceedings of ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp 573-581, ACM, 2011. (Best Student Paper Award; oral presentation, 7.8% acceptance rate; overall 17.5%)project website
Miettinen, P & Vreeken, J Model Order Selection for Boolean Matrix Factorization. In: Proceedings of ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp 51-59, ACM, 2011. (oral presentation, 7.8% acceptance rate; overall 17.5%)project website
Smets, K & Vreeken, J Identifying and Characterising Anomalies in Transaction Data. In: Proceedings of the 23rd Benelux Conference on Artificial Intelligence (BNAIC), ISSN 1568-7805, 2011. (extended abstract of our SDM'11 paper)
Smets, K & Vreeken, J The Odd One Out: Identifying and Characterising Anomalies. In: Proceedings of the SIAM International Conference on Data Mining (SDM), pp 804-815, SIAM, 2011. (25% acceptance rate)
Tatti, N & Vreeken, J Comparing Apples and Oranges – Measuring Differences between Data Mining Results. In: Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), pp 398-413, Springer, 2011. (invited for extension for best-of special issue, 3% acceptance rate; overall 20%)project websiteslidesvideo recording
2010
Mampaey, M & Vreeken, J Summarising Data by Clustering Items. In: Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), pp 321-336, Springer, 2010. (18% acceptance rate)project website
2009
Heikinheimo, H, Vreeken, J, Siebes, A & Mannila, H Low-Entropy Set Selection. In: Proceedings of the SIAM International Conference on Data Mining (SDM), pp 569-579, SIAM, 2009. (25% acceptance rate)
van Leeuwen, M, Vreeken, J & Siebes, A Identifying the Components. In: Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), pp 32-32, Springer, 2009. (ECMLPKDD'09 Best Student Paper)project websitevideo recording
2008
Tatti, N & Vreeken, J Finding Good Itemsets by Packing Data. In: Proceedings of the IEEE International Conference on Data Mining (ICDM), pp 588-597, IEEE, 2008. (9.8% acceptance rate)project website
Vreeken, J & Siebes, A Filling in the Blanks – Krimp Minimisation for Missing Data. In: Proceedings of the IEEE International Conference on Data Mining (ICDM), pp 1067-1072, IEEE, 2008. (19% acceptance rate)project website
2007
Siebes, A, van Leeuwen, M & Vreeken, J MDL for Pattern Mining. In: Proceedings of the International Conference on Statistics for Data Mining, Learning and Knowledge Extraction Models (IASC), 2007.project website
Vreeken, J, van Leeuwen, M & Siebes, A Preserving Privacy through Data Generation. In: Proceedings of the IEEE International Conference on Data Mining (ICDM), pp 685-690, IEEE, 2007. (19% acceptance rate)project website
Vreeken, J, van Leeuwen, M & Siebes, A Characterising the Difference. In: Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), pp 765-774, ACM, 2007. (19% acceptance rate)project website
2006
Siebes, A, Vreeken, J & van Leeuwen, M Item Sets That Compress. In: Proceedings of the SIAM International Conference on Data Mining (SDM), pp 393-404, SIAM, 2006. (16% acceptance rate)project website
van Leeuwen, M, Vreeken, J & Siebes, A Compression Picks the Item Sets that Matter. In: Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), pp 585-592, Springer, 2006. (18% acceptance rate)project website
2004
Wiering, M, Vreeken, J, van Veenen, J & Koopman, ACM Simulation and Optimization of Traffic in a City. In: Proceedings of the IEEE Intelligent Vehicles Symposium (IV), pp 453-458, IEEE, 2004.
Books & Proceedings
2019
Vreeken, J & Tatti, N (eds) Proceedings of the ACM SIGKDD Workshop on Learning and Mining for Cybersecurity (LEMINCS). , 2019.external project website
2016
Chau, DH, Vreeken, J, van Leeuwen, M, Shahaf, D & Faloutsos, C (eds) Proceedings of the ACM SIGKDD Workshop on Interactive Data Exploration and Analytics (IDEA). , 2016.external project website
Frasconi, P, Landwehr, N, Manco, G & Vreeken, J (eds) Proceedings of the European Conference on Machine Learning and Principles and Practices of Knowledge Discovery in Data (ECMLPKDD). Springer, 2016. (Part I)external project website
Frasconi, P, Landwehr, N, Manco, G & Vreeken, J (eds) Proceedings of the European Conference on Machine Learning and Principles and Practices of Knowledge Discovery in Data (ECMLPKDD). Springer, 2016. (Part II)external project website
2015
Chau, DH, Vreeken, J, van Leeuwen, M, Shahaf, D & Faloutsos, C (eds) Proceedings of the ACM SIGKDD Workshop on Interactive Data Exploration and Analytics (IDEA). , 2015.external project website
2014
Chau, DH, Vreeken, J, van Leeuwen, M & Faloutsos, C (eds) Proceedings of the ACM SIGKDD Workshop on Interactive Data Exploration and Analytics (IDEA). , 2014.external project website
2013
Chau, DH, Vreeken, J, van Leeuwen, M & Faloutsos, C (eds) Proceedings of the ACM SIGKDD Workshop on Interactive Data Exploration and Analytics (IDEA). ACM, 2013.external project website
2012
Vreeken, J, Ling, C, Zaki, MJ, Siebes, A, Yu, JX, Goethals, B, Webb, G & Wu, X (eds) Proceedings of the 12th IEEE International Conference on Data Mining Workshops (ICDMW). IEEE, 2012.external project website
Vreeken, J, van Leeuwen, M, Nijssen, S, Tatti, N, Dries, A & Goethals, B (eds) Proceedings of the ECML PKDD Workshop on Instant Interactive Data Mining (IID). , 2012.external project website
2010
Vreeken, J, Tatti, N & Goethals, B (eds) Proceedings of the ACM SIGKDD Workshop on Useful Patterns (UP). ACM Press, 2010.
2009
Vreeken, J Making Pattern Mining Useful. Dissertation, Universiteit Utrecht, 2009.project website
Bookchapters
2014
Vreeken, J & Tatti, N Interesting Patterns. In: Aggarwal, CC & Han, J (eds) Frequent Pattern Mining, pp 105-134, pp 105-134, Springer, 2014.
Zimek, A, Assent, I & Vreeken, J Frequent Pattern Mining Algorithms for Data Clustering. In: Aggarwal, CC & Han, J (eds) Frequent Pattern Mining, pp 403-424, pp 403-424, Springer, 2014.
van Leeuwen, M & Vreeken, J Mining and Using Sets of Patterns through Compression. In: Aggarwal, CC & Han, J (eds) Frequent Pattern Mining, pp 165-198, pp 165-198, Springer, 2014.
Workshop and Demo Papers
2022
Marx, A & Vreeken, J Formally Justifying MDL-based Inference of Cause and Effect. In: Proceedings of the AAAI Workshop on Information Theoretic Causal Inference and Discovery (ITCI'22), 2022.
Xu, S, Marx, A, Mian, O & Vreeken, J Causal Inference with Heteroscedastic Noise Models. In: Proceedings of the AAAI Workshop on Information Theoretic Causal Inference and Discovery (ITCI'22), 2022.project website
2019
Kalofolias, J, Boley, M & Vreeken, J Discovering Robustly Connected Subgraphs with Simple Descriptions. In: Proceedings of the ECMLPKDD Workshop on Graph Embedding and Mining (GEM), 2019. (oral presentation, 21% acceptance rate)project website
Kalofolias, J, Boley, M & Vreeken, J Discovering Robustly Connected Subgraphs with Simple Descriptions. In: Proceedings of the ACM SIGKDD Workshop on Mining and Learning from Graphs (MLG), 2019.project website
Marx, A & Vreeken, J Approximating Algorithmic Conditional Independence for Discrete Data. In: Proceedings of the the First AAAI Spring Symposium Beyond Curve Fitting: Causation, Counterfactuals, and Imagination-based AI, AAAI, 2019.project website
Saran, D & Vreeken, J Summarizing Dynamic Graphs using MDL. In: Proceedings of the ECMLPKDD Workshop on Graph Embedding and Mining (GEM), 2019. (oral presentation, 21% acceptance rate)
2018
Budhathoki, K, Boley, M & Vreeken, J Rule Discovery for Exploratory Causal Reasoning. In: Proceedings of the NeurIPS 2018 workshop on Causal Learning, pp 1-14, 2018.
Marx, A & Vreeken, J Stochastic Complexity for Testing Conditional Independence on Discrete Data. In: Proceedings of the NeurIPS 2018 workshop on Causal Learning, pp 1-12, 2018.project website
2017
Grosse, K & Vreeken, J Summarising Event Sequences using Serial Episodes and an Ontology. In: Proceedings of the 4th Workshop on Interactions between Data Mining and Natural Language Processing (DMNLP'17), pp 33-48, CEUR Workshop Proceedings, 2017.
Hinrichs, F & Vreeken, J Characterising the Difference and the Norm between Sequences Databases. In: Proceedings of the 4th Workshop on Interactions between Data Mining and Natural Language Processing (DMNLP'17), pp 49-64, CEUR Workshop Proceedings, 2017.
2014
Athukorala, K, Oulasvirta, A, Glowacka, D, Vreeken, J & Jacucci, G Supporting Exploratory Search Through User Modeling. In: Proceedings of the UMAP Joint Workshop on Personalized Information Access (PIA), pp 1-6, 2014.
Athukorala, K, Oulasvirta, A, Glowacka, D, Vreeken, J & Jacucci, G Interaction Model to Predict Subjective-Specificity of Search Results. In: Proceedings of the 22nd Conference on User Modeling, Adaptation and Personalization — Late-Breaking Results (UMAP), pp 1-6, 2014.
Gandhi, M & Vreeken, J Slimmer, outsmarting Slim. PhD Poster and Video at: the 13th International Symposium on Intelligent Data Analysis (IDA), Springer, 2014.project websiteslidesvideo recording
2012
Akoglu, L, Vreeken, J, Tong, H, Chau, DH & Faloutsos, C Mining and Visualizing Connection Pathways in Large Information Networks. In: Proceedings of the Workshop on Information in Networks (WIN), pp 1-3, 2012.project websiteslides
Vreeken, J & Tatti, N Summarising Event Sequences with Serial Episodes. In: Proceedings of the 5th Workshop on Information Theoretic Methods in Science and Engineering (WITMSE), pp 82-85, 2012. (invited contribution, extended abstract of our KDD'12 paper)project websiteslides
Wu, H, Mampaey, M, Tatti, N, Vreeken, J, Hossain, MS & Ramakrishnan, N Where Do I Start? Algorithmic Strategies to Guide Intelligence Analysts. In: Proceedings of the ACM SIGKDD Workshop on Intelligence and Security Informatics (ISI-KDD), pp 1-8, ACM, 2012.
Chau, DH, Akoglu, L, Vreeken, J, Tong, H & Faloutsos, C Interactively and Visually Exploring Tours of Marked Nodes in Large Graphs. Demo at, and included in: Proceedings of IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), ACM, 2012.project website
Chau, DH, Akoglu, L, Vreeken, J, Tong, H & Faloutsos, C TourViz: Interactive Visualization of Connection Pathways in Large Graphs. Demo at, and included in: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp 1516-1519, ACM, 2012.project websiteslides
2011
Vreeken, J & Zimek, A When Pattern Met Subspace Cluster - A Relationship Story. In: Proceedings of the 2nd Workshop on Discovering, Summarizing and Using Multiple Clusterings (MultiClust), pp 7-18, 2011.
Goethals, B, Moens, S & Vreeken, J mime: A Framework for Interactive Visual Pattern Mining. Demo at, and included in: Proceedings of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), pp 634-637, Springer, 2011.external project website
Goethals, B, Moens, S & Vreeken, J mime: A Framework for Interactive Visual Pattern Mining. Demo at, and included in: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp 757-760, ACM, 2011.external project website
2003
Koopman, ACM, van Leeuwen, M & Vreeken, J Exploring Temporal Memory of LSTM and Spiking Circuits. In: Workshop on the Future of Neural Networks (FUNN), 2003.
Tutorials
2019
Vreeken, J & Yamanishi, K Modern MDL meets Data Mining Insights, Theory, and Practice. At the SIAM International Conference on Data Mining (SDM), 2019.external project website
2018
Koutra, DVJ & Bonchi, F Summarizing Graphs at Multiple Scales: New Trends. At the SIAM International Conference on Data Mining (SDM), 2018.external project website
2015
Siebes, A, van Leeuwen, M & Vreeken, J Information Theoretic Methods in Data Mining. At the SIAM International Conference on Data Mining (SDM), 2015.external project website
2014
Siebes, A, van Leeuwen, M & Vreeken, J Information Theoretic Methods in Data Mining. At the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Nancy, France, 2014.
2011
Bringmann, B, Nijssen, S, Tatti, N, Vreeken, J & Zimmermann, A Mining Sets of Patterns - Next Generation Pattern Mining. At the IEEE International Conference on Data Mining (ICDM), Vancouver, Canada, 2011.
2010
Bringmann, B, Nijssen, S, Tatti, N, Vreeken, J & Zimmermann, A Mining Sets of Patterns. At the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Barcelona, Spain, 2010.video recording
Unrefereed Publications
2024
Xu, S, Cueppers, J & Vreeken, J Succinct Interaction-Aware Explanations. Technical Report 2402.05566, arXiv, 2024.project website
2018
Marx, A & Vreeken, J Causal Discovery by Telling Apart Parents and Children. Technical Report 1808.06356, arXiv, 2018.project website
2013
Akoglu, L, Vreeken, J, Tong, H, Chau, DH, Tatti, N & Faloutsos, C Islands and Bridges: Making Sense of Marked Nodes in Large Graphs. Technical Report CMU-CS-12-124R, Carnegie Mellon University, 2013.project website
2012
Miettinen, P & Vreeken, J mdl4bmf: Minimum Description Length for Boolean Matrix Factorization. Technical Report MPI-I-2012-5-001, Max-Planck-Institut für Informatik, 2012.project website
2011
Tatti, N & Vreeken, J Comparing Apples and Oranges – Measuring Differences between Data Mining Results. Technical Report UA-CS-2011-03, Universiteit Antwerpen, 2011.project website
2008
Vreeken, J & Siebes, A Krimp Minimisation for Missing Data Estimation. Technical Report UU-CS-2008-034, Universiteit Utrecht, 2008.project website
2006
van Leeuwen, M, Vreeken, J & Siebes, A Compression Picks the Significant Item Sets. Technical Report UU-CS-2006-050, Universiteit Utrecht, 2006.project website
2004
Wiering, MA, van Veenen, J, Vreeken, J & Koopman, ACM Intelligent Traffic Light Control. Technical Report UU-CS-2004-029, Universiteit Utrecht, 2004.
Vreeken, J On real-world temporal pattern recognition using Liquid State Machines. M.Sc. Thesis, Universiteit Utrecht, 2004.
2002
Vreeken, J Spiking neural networks, an introduction. Technical Report UU-CS-2003-008, Universiteit Utrecht, 2002.