Jilles Vreeken

Orcid: 0000-0002-2310-2806

Affiliations:
  • CISPA Helmholtz Center for Information Security, Saarbrücken, Germany
  • Saarland University, Saarbrücken, Germany


According to our database1, Jilles Vreeken authored at least 148 papers between 2006 and 2024.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
All the world's a (hyper)graph: A data drama.
Digit. Scholarsh. Humanit., 2024

The Uncanny Valley: Exploring Adversarial Robustness from a Flatness Perspective.
CoRR, 2024

Learning Exceptional Subgroups by End-to-End Maximizing KL-divergence.
CoRR, 2024

Succint Interaction-Aware Explanations.
CoRR, 2024

Identifying Confounding from Causal Mechanism Shifts.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

What Are the Rules? Discovering Constraints from Data.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Finding Interpretable Class-Specific Patterns through Efficient Neural Search.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Discovering Sequential Patterns with Predictable Inter-event Delays.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Data is Moody: Discovering Data Modification Rules from Process Event Logs.
CoRR, 2023

Understanding and Mitigating Classification Errors Through Interpretable Token Patterns.
CoRR, 2023

Preserving local densities in low-dimensional embeddings.
CoRR, 2023

Causal Discovery with Hidden Confounders using the Algorithmic Markov Condition.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Why Are We Waiting? Discovering Interpretable Models for Predicting Sojourn and Waiting Times.
Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

Learning Causal Models under Independent Changes.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Below the Surface: Summarizing Event Sequences with Generalized Sequential Patterns.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Nonlinear Causal Discovery with Latent Confounders.
Proceedings of the International Conference on Machine Learning, 2023

Federated Learning from Small Datasets.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Towards Concept-Aware Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Nothing but Regrets - Privacy-Preserving Federated Causal Discovery.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Information-Theoretic Causal Discovery and Intervention Detection over Multiple Environments.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Identifying Selection Bias from Observational Data.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Omen: discovering sequential patterns with reliable prediction delays.
Knowl. Inf. Syst., 2022

Efficiently Factorizing Boolean Matrices using Proximal Gradient Descent.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Discovering Invariant and Changing Mechanisms from Data.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Discovering Significant Patterns under Sequential False Discovery Control.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Inferring Cause and Effect in the Presence of Heteroscedastic Noise.
Proceedings of the International Conference on Machine Learning, 2022

Label-Descriptive Patterns and Their Application to Characterizing Classification Errors.
Proceedings of the International Conference on Machine Learning, 2022

Discovering Interpretable Data-to-Sequence Generators.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Naming the Most Anomalous Cluster in Hilbert Space for Structures with Attribute Information.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Differentially Describing Groups of Graphs.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Formally Justifying MDL-based Inference of Cause and Effect.
CoRR, 2021

Factoring out prior knowledge from low-dimensional embeddings.
CoRR, 2021

Mining Easily Understandable Models from Complex Event Logs.
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

SUSAN: The Structural Similarity Random Walk Kernel.
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Discovering Reliable Causal Rules.
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Differentiable Pattern Set Mining.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Graph Similarity Description: How Are These Graphs Similar?
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

What's in the Box? Exploring the Inner Life of Neural Networks with Robust Rules.
Proceedings of the 38th International Conference on Machine Learning, 2021

Discovering Fully Oriented Causal Networks.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Discovering dependencies with reliable mutual information.
Knowl. Inf. Syst., 2020

What is Normal, What is Strange, and What is Missing in a Knowledge Graph: Unified Characterization via Inductive Summarization.
Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

Towards Plausible Graph Anonymization.
Proceedings of the 27th Annual Network and Distributed System Security Symposium, 2020

Discovering Approximate Functional Dependencies using Smoothed Mutual Information.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Discovering Functional Dependencies from Mixed-Type Data.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Discovering Succinct Pattern Sets Expressing Co-Occurrence and Mutual Exclusivity.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

The Relaxed Maximum Entropy Distribution and its Application to Pattern Discovery.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Just Wait For It... Mining Sequential Patterns with Reliable Prediction Delays.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Explainable Data Decompositions.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Addendum to the Special Issue on Interactive Data Exploration and Analytics (TKDD, Vol. 12 Iss. 1).
ACM Trans. Knowl. Discov. Data, 2019

Telling cause from effect by local and global regression.
Knowl. Inf. Syst., 2019

We Are Not Your Real Parents: Telling Causal from Confounded using MDL.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Sets of Robust Rules, and How to Find Them.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

Modern MDL meets Data Mining Insights, Theory, and Practice.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Identifiability of Cause and Effect using Regularized Regression.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Discovering Reliable Correlations in Categorical Data.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Discovering Robustly Connected Subgraphs with Simple Descriptions.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Testing Conditional Independence on Discrete Data using Stochastic Complexity.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Generating Realistic Synthetic Population Datasets.
ACM Trans. Knowl. Discov. Data, 2018

Origo: causal inference by compression.
Knowl. Inf. Syst., 2018

Causal Discovery by Telling Apart Parents and Children.
CoRR, 2018

JAMI: fast computation of conditional mutual information for ceRNA network analysis.
Bioinform., 2018

Causal Inference on Event Sequences.
Proceedings of the 2018 SIAM International Conference on Data Mining, 2018

Causal Inference on Multivariate and Mixed-Type Data.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Discovering Reliable Dependencies from Data: Hardness and Improved Algorithms.
Proceedings of the IEEE International Conference on Data Mining, 2018

Summarizing Graphs at Multiple Scales: New Trends.
Proceedings of the IEEE International Conference on Data Mining, 2018

Accurate Causal Inference on Discrete Data.
Proceedings of the IEEE International Conference on Data Mining, 2018

2017
Identifying consistent statements about numerical data with dispersion-corrected subgroup discovery.
Data Min. Knowl. Discov., 2017

Beyond Pairwise Similarity: Quantifying and Characterizing Linguistic Similarity between Groups of Languages by MDL.
Computación y Sistemas, 2017

CTRL+Z: Recovering Anonymized Social Graphs.
CoRR, 2017

Causal Inference on Multivariate Mixed-Type Data by Minimum Description Length.
CoRR, 2017

Causal Inference by Stochastic Complexity.
CoRR, 2017

FACETS: Adaptive Local Exploration of Large Graphs.
Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Correlation by Compression.
Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Efficiently Summarising Event Sequences with Rich Interleaving Patterns.
Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Efficiently Discovering Unexpected Pattern-Co-Occurrences.
Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Discovering Reliable Approximate Functional Dependencies.
Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Telling Cause from Effect Using MDL-Based Local and Global Regression.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Efficiently Discovering Locally Exceptional Yet Globally Representative Subgroups.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

MDL for Causal Inference on Discrete Data.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

2016
Is exploratory search different? A comparison of information search behavior for exploratory and lookup tasks.
J. Assoc. Inf. Sci. Technol., 2016

Interactive and Iterative Discovery of Entity Network Subgraphs.
CoRR, 2016

Linear-time Detection of Non-linear Changes in Massively High Dimensional Time Series.
Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Flexibly Mining Better Subgroups.
Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Universal Dependency Analysis.
Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Reconstructing an Epidemic Over Time.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Keeping it Short and Simple: Summarising Complex Event Sequences with Multivariate Patterns.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Causal Inference by Compression.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

2015
Summarizing and understanding large graphs.
Stat. Anal. Data Min., 2015

The blind men and the elephant: on meeting the problem of multiple truths in data from clustering and pattern mining perspectives.
Mach. Learn., 2015

Erratum to: Unsupervised interaction-preserving discretization of multivariate data.
Data Min. Knowl. Discov., 2015

Seeing the Forest through the Trees: Adaptive Local Exploration of Large Graphs.
CoRR, 2015

Universal Dependency Analysis.
CoRR, 2015

Canonical Divergence Analysis.
CoRR, 2015

Beauty and Brains: Detecting Anomalous Pattern Co-Occurrences.
CoRR, 2015

Causal Inference by Direction of Information.
Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

Hidden Hazards: Finding Missing Nodes in Large Graph Epidemics.
Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

Getting to Know the Unknown Unknowns: Destructive-Noise Resistant Boolean Matrix Factorization.
Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

Non-parametric Jensen-Shannon Divergence.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

The Difference and the Norm - Characterising Similarities and Differences Between Databases.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

2014
MDL4BMF: Minimum Description Length for Boolean Matrix Factorization.
ACM Trans. Knowl. Discov. Data, 2014

Efficiently spotting the starting points of an epidemic in a large graph.
Knowl. Inf. Syst., 2014

Uncovering the plot: detecting surprising coalitions of entities in multi-relational schemas.
Data Min. Knowl. Discov., 2014

Unsupervised interaction-preserving discretization of multivariate data.
Data Min. Knowl. Discov., 2014

Supporting Exploratory Search Through User Modeling.
Proceedings of the Posters, 2014

Interaction Model to Predict Subjective-Specificity of Search Results.
Proceedings of the Posters, 2014

VOG: Summarizing and Understanding Large Graphs.
Proceedings of the 2014 SIAM International Conference on Data Mining, 2014

Multivariate Maximal Correlation Analysis.
Proceedings of the 31th International Conference on Machine Learning, 2014

A Fresh Look on Knowledge Bases: Distilling Named Events from News.
Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 2014

Narrow or Broad?: Estimating Subjective Specificity in Exploratory Search.
Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 2014

Frequent Pattern Mining Algorithms for Data Clustering.
Proceedings of the Frequent Pattern Mining, 2014

Interesting Patterns.
Proceedings of the Frequent Pattern Mining, 2014

Mining and Using Sets of Patterns through Compression.
Proceedings of the Frequent Pattern Mining, 2014

2013
Efficient Discovery of the Most Interesting Associations.
ACM Trans. Knowl. Discov. Data, 2013

Summarizing categorical data by clustering attributes.
Data Min. Knowl. Discov., 2013

CMI: An Information-Theoretic Contrast Measure for Enhancing Subspace Cluster and Outlier Detection.
Proceedings of the 13th SIAM International Conference on Data Mining, 2013

Mining Connection Pathways for Marked Nodes in Large Graphs.
Proceedings of the 13th SIAM International Conference on Data Mining, 2013

Detecting Bicliques in GF[q].
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Maximum Entropy Models for Iteratively Identifying Subjectively Interesting Structure in Real-Valued Data.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Cartification: A Neighborhood Preserving Transformation for Mining High Dimensional Data.
Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

2012
Summarizing data succinctly with the most informative itemsets.
ACM Trans. Knowl. Discov. Data, 2012

Comparing apples and oranges: measuring differences between exploratory data mining results.
Data Min. Knowl. Discov., 2012

Slim: Directly Mining Descriptive Patterns.
Proceedings of the Twelfth SIAM International Conference on Data Mining, 2012

Discovering Descriptive Tile Trees - By Mining Optimal Geometric Subtiles.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

The long and the short of it: summarising event sequences with serial episodes.
Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

TourViz: interactive visualization of connection pathways in large graphs.
Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Spotting Culprits in Epidemics: How Many and Which Ones?
Proceedings of the 12th IEEE International Conference on Data Mining, 2012

Fast and reliable anomaly detection in categorical data.
Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012

Interactively and Visually Exploring Tours of Marked Nodes in Large Graphs.
Proceedings of the International Conference on Advances in Social Networks Analysis and Mining, 2012

2011
Krimp: mining itemsets that compress.
Data Min. Knowl. Discov., 2011

The Odd One Out: Identifying and Characterising Anomalies.
Proceedings of the Eleventh SIAM International Conference on Data Mining, 2011

Comparing Apples and Oranges - Measuring Differences between Data Mining Results.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

MIME: A Framework for Interactive Visual Pattern Mining.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

When Pattern Met Subspace Cluster.
Proceedings of the 2nd MultiClust Workshop: Discovering, 2011

Model order selection for boolean matrix factorization.
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

Tell me what i need to know: succinctly summarizing data with itemsets.
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

Maximum Entropy Modelling for Assessing Results on Real-Valued Data.
Proceedings of the 11th IEEE International Conference on Data Mining, 2011

2010
Useful patterns (UP'10) ACM SIGKDD workshop report.
SIGKDD Explor., 2010

Making pattern mining useful.
SIGKDD Explor., 2010

Summarising Data by Clustering Items.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

2009
Making Pattern Mining Useful.
PhD thesis, 2009

Identifying the components.
Data Min. Knowl. Discov., 2009

Low-Entropy Set Selection.
Proceedings of the SIAM International Conference on Data Mining, 2009

2008
Filling in the Blanks - Krimp Minimisation for Missing Data.
Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

Finding Good Itemsets by Packing Data.
Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

2007
Characterising the difference.
Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2007

Preserving Privacy through Data Generation.
Proceedings of the 7th IEEE International Conference on Data Mining (ICDM 2007), 2007

2006
Item Sets that Compress.
Proceedings of the Sixth SIAM International Conference on Data Mining, 2006

Compression Picks Item Sets That Matter.
Proceedings of the Knowledge Discovery in Databases: PKDD 2006, 2006


  Loading...