Jilles Vreeken

Bastian Rieck

Digit. Scholarsh. Humanit., 2024

Learning Exceptional Subgroups by End-to-End Maximizing KL-divergence.

[BibT_eX]

[DOI]

CoRR, 2024

Succint Interaction-Aware Explanations.

[BibT_eX]

[DOI]

Sascha Xu

CoRR, 2024

What Are the Rules? Discovering Constraints from Data.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Finding Interpretable Class-Specific Patterns through Efficient Neural Search.

[BibT_eX]

[DOI]

Nils Philipp Walter

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Discovering Sequential Patterns with Predictable Inter-event Delays.

[BibT_eX]

[DOI]

Paul Krieger

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

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

[BibT_eX]

[DOI]

Marco Bjarne Schuster

CoRR, 2023

Understanding and Mitigating Classification Errors Through Interpretable Token Patterns.

[BibT_eX]

[DOI]

CoRR, 2023

Preserving local densities in low-dimensional embeddings.

[BibT_eX]

[DOI]

Rebekka Burkholz

CoRR, 2023

Causal Discovery with Hidden Confounders using the Algorithmic Markov Condition.

[BibT_eX]

[DOI]

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Why Are We Waiting? Discovering Interpretable Models for Predicting Sojourn and Waiting Times.

[BibT_eX]

[DOI]

Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

Learning Causal Models under Independent Changes.

[BibT_eX]

[DOI]

Sarah Mameche

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.

[BibT_eX]

[DOI]

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Nonlinear Causal Discovery with Latent Confounders.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

Federated Learning from Small Datasets.

[BibT_eX]

[DOI]

Michael Kamp

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Towards Concept-Aware Large Language Models.

[BibT_eX]

[DOI]

Chen Shani

Dafna Shahaf

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Nothing but Regrets - Privacy-Preserving Federated Causal Discovery.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Information-Theoretic Causal Discovery and Intervention Detection over Multiple Environments.

[BibT_eX]

[DOI]

Osman Mian

Michael Kamp

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Identifying Selection Bias from Observational Data.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Omen: discovering sequential patterns with reliable prediction delays.

[BibT_eX]

[DOI]

Knowl. Inf. Syst., 2022

Efficiently Factorizing Boolean Matrices using Proximal Gradient Descent.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Sarah Mameche

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Label-Descriptive Patterns and Their Application to Characterizing Classification Errors.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Discovering Interpretable Data-to-Sequence Generators.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Naming the Most Anomalous Cluster in Hilbert Space for Structures with Attribute Information.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Differentially Describing Groups of Graphs.

[BibT_eX]

[DOI]

Corinna Coupette

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Formally Justifying MDL-based Inference of Cause and Effect.

[BibT_eX]

[DOI]

CoRR, 2021

Factoring out prior knowledge from low-dimensional embeddings.

[BibT_eX]

[DOI]

Edith Heiter

CoRR, 2021

Mining Easily Understandable Models from Complex Event Logs.

[BibT_eX]

[DOI]

Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

SUSAN: The Structural Similarity Random Walk Kernel.

[BibT_eX]

[DOI]

Pascal Welke

Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Discovering Reliable Causal Rules.

[BibT_eX]

[DOI]

Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Differentiable Pattern Set Mining.

[BibT_eX]

[DOI]

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?

[BibT_eX]

[DOI]

Corinna Coupette

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.

[BibT_eX]

[DOI]

Anna Oláh

Proceedings of the 38th International Conference on Machine Learning, 2021

Discovering Fully Oriented Causal Networks.

[BibT_eX]

[DOI]

Osman Mian

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Discovering dependencies with reliable mutual information.

[BibT_eX]

[DOI]

Knowl. Inf. Syst., 2020

What is Normal, What is Strange, and What is Missing in a Knowledge Graph: Unified Characterization via Inductive Summarization.

[BibT_eX]

[DOI]

Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

Towards Plausible Graph Anonymization.

[BibT_eX]

[DOI]

Proceedings of the 27th Annual Network and Distributed System Security Symposium, 2020

Discovering Approximate Functional Dependencies using Smoothed Mutual Information.

[BibT_eX]

[DOI]

Frédéric Pennerath

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Discovering Functional Dependencies from Mixed-Type Data.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Just Wait For It... Mining Sequential Patterns with Reliable Prediction Delays.

[BibT_eX]

[DOI]

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Explainable Data Decompositions.

[BibT_eX]

[DOI]

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).

[BibT_eX]

[DOI]

ACM Trans. Knowl. Discov. Data, 2019

Telling cause from effect by local and global regression.

[BibT_eX]

[DOI]

Knowl. Inf. Syst., 2019

We Are Not Your Real Parents: Telling Causal from Confounded using MDL.

[BibT_eX]

[DOI]

Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Sets of Robust Rules, and How to Find Them.

[BibT_eX]

[DOI]

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

Modern MDL meets Data Mining Insights, Theory, and Practice.

[BibT_eX]

[DOI]

Kenji Yamanishi

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Identifiability of Cause and Effect using Regularized Regression.

[BibT_eX]

[DOI]

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Discovering Reliable Correlations in Categorical Data.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Discovering Robustly Connected Subgraphs with Simple Descriptions.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Testing Conditional Independence on Discrete Data using Stochastic Complexity.

[BibT_eX]

[DOI]

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Generating Realistic Synthetic Population Datasets.

[BibT_eX]

[DOI]

Hao Wu

Yue Ning

Prithwish Chakraborty

Naren Ramakrishnan

ACM Trans. Knowl. Discov. Data, 2018

Origo: causal inference by compression.

[BibT_eX]

[DOI]

Knowl. Inf. Syst., 2018

Causal Discovery by Telling Apart Parents and Children.

[BibT_eX]

[DOI]

CoRR, 2018

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

[BibT_eX]

[DOI]

Bioinform., 2018

Causal Inference on Event Sequences.

[BibT_eX]

[DOI]

Proceedings of the 2018 SIAM International Conference on Data Mining, 2018

Causal Inference on Multivariate and Mixed-Type Data.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

Discovering Reliable Dependencies from Data: Hardness and Improved Algorithms.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Data Mining, 2018

Summarizing Graphs at Multiple Scales: New Trends.

[BibT_eX]

[DOI]

Danai Koutra

Francesco Bonchi

Proceedings of the IEEE International Conference on Data Mining, 2018

Accurate Causal Inference on Discrete Data.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Data Mining, 2018

2017

Identifying consistent statements about numerical data with dispersion-corrected subgroup discovery.

[BibT_eX]

[DOI]

Data Min. Knowl. Discov., 2017

Beyond Pairwise Similarity: Quantifying and Characterizing Linguistic Similarity between Groups of Languages by MDL.

[BibT_eX]

[DOI]

Andrea K. Fischer

Computación y Sistemas, 2017

CTRL+Z: Recovering Anonymized Social Graphs.

[BibT_eX]

[DOI]

CoRR, 2017

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

[BibT_eX]

[DOI]

CoRR, 2017

Causal Inference by Stochastic Complexity.

[BibT_eX]

[DOI]

CoRR, 2017

FACETS: Adaptive Local Exploration of Large Graphs.

[BibT_eX]

[DOI]

Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Correlation by Compression.

[BibT_eX]

[DOI]

Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Efficiently Summarising Event Sequences with Rich Interleaving Patterns.

[BibT_eX]

[DOI]

Apratim Bhattacharyya

Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Efficiently Discovering Unexpected Pattern-Co-Occurrences.

[BibT_eX]

[DOI]

Roel Bertens

Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Discovering Reliable Approximate Functional Dependencies.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Efficiently Discovering Locally Exceptional Yet Globally Representative Subgroups.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

MDL for Causal Inference on Discrete Data.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

J. Assoc. Inf. Sci. Technol., 2016

Interactive and Iterative Discovery of Entity Network Subgraphs.

[BibT_eX]

[DOI]

CoRR, 2016

Linear-time Detection of Non-linear Changes in Massively High Dimensional Time Series.

[BibT_eX]

[DOI]

Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Flexibly Mining Better Subgroups.

[BibT_eX]

[DOI]

Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Universal Dependency Analysis.

[BibT_eX]

[DOI]

Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Reconstructing an Epidemic Over Time.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Roel Bertens

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Causal Inference by Compression.

[BibT_eX]

[DOI]

Proceedings of the IEEE 16th International Conference on Data Mining, 2016

2015

Summarizing and understanding large graphs.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Arthur Zimek

Mach. Learn., 2015

Erratum to: Unsupervised interaction-preserving discretization of multivariate data.

[BibT_eX]

[DOI]

Data Min. Knowl. Discov., 2015

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

[BibT_eX]

[DOI]

CoRR, 2015

Universal Dependency Analysis.

[BibT_eX]

[DOI]

CoRR, 2015

Canonical Divergence Analysis.

[BibT_eX]

[DOI]

CoRR, 2015

Beauty and Brains: Detecting Anomalous Pattern Co-Occurrences.

[BibT_eX]

[DOI]

Roel Bertens

CoRR, 2015

Causal Inference by Direction of Information.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Shashidhar Sundareisan

B. Aditya Prakash

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.

[BibT_eX]

[DOI]

Sanjar Karaev

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

Non-parametric Jensen-Shannon Divergence.

[BibT_eX]

[DOI]

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

The Difference and the Norm - Characterising Similarities and Differences Between Databases.

[BibT_eX]

[DOI]

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

2014

MDL4BMF: Minimum Description Length for Boolean Matrix Factorization.

[BibT_eX]

[DOI]

ACM Trans. Knowl. Discov. Data, 2014

Efficiently spotting the starting points of an epidemic in a large graph.

[BibT_eX]

[DOI]

B. Aditya Prakash

Christos Faloutsos

Knowl. Inf. Syst., 2014

Uncovering the plot: detecting surprising coalitions of entities in multi-relational schemas.

[BibT_eX]

[DOI]

Data Min. Knowl. Discov., 2014

Unsupervised interaction-preserving discretization of multivariate data.

[BibT_eX]

[DOI]

Data Min. Knowl. Discov., 2014

Supporting Exploratory Search Through User Modeling.

[BibT_eX]

[DOI]

Proceedings of the Posters, 2014

Interaction Model to Predict Subjective-Specificity of Search Results.

[BibT_eX]

[DOI]

Proceedings of the Posters, 2014

VOG: Summarizing and Understanding Large Graphs.

[BibT_eX]

[DOI]

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

Multivariate Maximal Correlation Analysis.

[BibT_eX]

[DOI]

Proceedings of the 31th International Conference on Machine Learning, 2014

A Fresh Look on Knowledge Bases: Distilling Named Events from News.

[BibT_eX]

[DOI]

Erdal Kuzey

Gerhard Weikum

Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 2014

Narrow or Broad?: Estimating Subjective Specificity in Exploratory Search.

[BibT_eX]

[DOI]

Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, 2014

Frequent Pattern Mining Algorithms for Data Clustering.

[BibT_eX]

[DOI]

Arthur Zimek

Ira Assent

Proceedings of the Frequent Pattern Mining, 2014

Interesting Patterns.

[BibT_eX]

[DOI]

Proceedings of the Frequent Pattern Mining, 2014

Mining and Using Sets of Patterns through Compression.

[BibT_eX]

[DOI]

Proceedings of the Frequent Pattern Mining, 2014

2013

Efficient Discovery of the Most Interesting Associations.

[BibT_eX]

[DOI]

Geoffrey I. Webb

ACM Trans. Knowl. Discov. Data, 2013

Summarizing categorical data by clustering attributes.

[BibT_eX]

[DOI]

Data Min. Knowl. Discov., 2013

CMI: An Information-Theoretic Contrast Measure for Enhancing Subspace Cluster and Outlier Detection.

[BibT_eX]

[DOI]

Proceedings of the 13th SIAM International Conference on Data Mining, 2013

Mining Connection Pathways for Marked Nodes in Large Graphs.

[BibT_eX]

[DOI]

Proceedings of the 13th SIAM International Conference on Data Mining, 2013

Detecting Bicliques in GF[q].

[BibT_eX]

[DOI]

Jan Ramon

Kleanthis-Nikolaos Kontonasios

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Maximum Entropy Models for Iteratively Identifying Subjectively Interesting Structure in Real-Valued Data.

[BibT_eX]

[DOI]

Tijl De Bie

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Cartification: A Neighborhood Preserving Transformation for Mining High Dimensional Data.

[BibT_eX]

[DOI]

Proceedings of the 2013 IEEE 13th International Conference on Data Mining, 2013

2012

Summarizing data succinctly with the most informative itemsets.

[BibT_eX]

[DOI]

ACM Trans. Knowl. Discov. Data, 2012

Comparing apples and oranges: measuring differences between exploratory data mining results.

[BibT_eX]

[DOI]

Data Min. Knowl. Discov., 2012

Slim: Directly Mining Descriptive Patterns.

[BibT_eX]

[DOI]

Koen Smets

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

Discovering Descriptive Tile Trees - By Mining Optimal Geometric Subtiles.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

The long and the short of it: summarising event sequences with serial episodes.

[BibT_eX]

[DOI]

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

TourViz: interactive visualization of connection pathways in large graphs.

[BibT_eX]

[DOI]

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

Spotting Culprits in Epidemics: How Many and Which Ones?

[BibT_eX]

[DOI]

B. Aditya Prakash

Christos Faloutsos

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

Fast and reliable anomaly detection in categorical data.

[BibT_eX]

[DOI]

Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012

Interactively and Visually Exploring Tours of Marked Nodes in Large Graphs.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Advances in Social Networks Analysis and Mining, 2012

2011

Krimp: mining itemsets that compress.

[BibT_eX]

[DOI]

Data Min. Knowl. Discov., 2011

The Odd One Out: Identifying and Characterising Anomalies.

[BibT_eX]

[DOI]

Koen Smets

Proceedings of the Eleventh SIAM International Conference on Data Mining, 2011

Comparing Apples and Oranges - Measuring Differences between Data Mining Results.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

MIME: A Framework for Interactive Visual Pattern Mining.

[BibT_eX]

[DOI]

Bart Goethals

Sandy Moens

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2011

When Pattern Met Subspace Cluster.

[BibT_eX]

[DOI]

Arthur Zimek

Proceedings of the 2nd MultiClust Workshop: Discovering, 2011

Model order selection for boolean matrix factorization.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Kleanthis-Nikolaos Kontonasios

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.

[BibT_eX]

[DOI]

Tijl De Bie

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

2010

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

[BibT_eX]

[DOI]

Bart Goethals

SIGKDD Explor., 2010

Making pattern mining useful.

[BibT_eX]

[DOI]

SIGKDD Explor., 2010

Summarising Data by Clustering Items.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

2009

Making Pattern Mining Useful.

[BibT_eX]

[DOI]

PhD thesis, 2009

Identifying the components.

[BibT_eX]

[DOI]

Data Min. Knowl. Discov., 2009

Low-Entropy Set Selection.

[BibT_eX]

[DOI]

Proceedings of the SIAM International Conference on Data Mining, 2009

2008

Filling in the Blanks - Krimp Minimisation for Missing Data.

[BibT_eX]

[DOI]

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

Finding Good Itemsets by Packing Data.

[BibT_eX]

[DOI]

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

2007

Characterising the difference.

[BibT_eX]

[DOI]

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

Preserving Privacy through Data Generation.

[BibT_eX]

[DOI]

Proceedings of the 7th IEEE International Conference on Data Mining (ICDM 2007), 2007

2006

Item Sets that Compress.

[BibT_eX]

[DOI]

Proceedings of the Sixth SIAM International Conference on Data Mining, 2006

Compression Picks Item Sets That Matter.

[BibT_eX]

[DOI]