
Graph Similarity Description: How Are These Graphs Similar?
How do social networks differ across platforms? How do information netwo...
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Formally Justifying MDLbased Inference of Cause and Effect
The algorithmic independence of conditionals, which postulates that the ...
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Factoring out prior knowledge from lowdimensional embeddings
Lowdimensional embedding techniques such as tSNE and UMAP allow visuali...
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Discovering Reliable Causal Rules
We study the problem of deriving policies, or rules, that when enacted o...
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What is Normal, What is Strange, and What is Missing in a Knowledge Graph: Unified Characterization via Inductive Summarization
Knowledge graphs (KGs) store highly heterogeneous information about the ...
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Discovering Reliable Correlations in Categorical Data
In many scientific tasks we are interested in discovering whether there ...
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Summarizing Data Succinctly with the Most Informative Itemsets
Knowledge discovery from data is an inherently iterative process. That i...
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Tell Me What I Need to Know: Succinctly Summarizing Data with Itemsets
Data analysis is an inherently iterative process. That is, what we know ...
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Testing Conditional Independence on Discrete Data using Stochastic Complexity
Testing for conditional independence is a core aspect of constraintbase...
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Comparing Apples and Oranges: Measuring Differences between Exploratory Data Mining Results
Deciding whether the results of two different mining algorithms provide ...
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Comparing Apples and Oranges: Measuring Differences between Data Mining Results
Deciding whether the results of two different mining algorithms provide ...
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Discovering Descriptive Tile Trees by Mining Optimal Geometric Subtiles
When analysing binary data, the ease at which one can interpret results ...
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The Long and the Short of It: Summarising Event Sequences with Serial Episodes
An ideal outcome of pattern mining is a small set of informative pattern...
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Finding Good Itemsets by Packing Data
The problem of selecting small groups of itemsets that represent the dat...
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We Are Not Your Real Parents: Telling Causal from Confounded using MDL
Given data over variables (X_1,...,X_m, Y) we consider the problem of fi...
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Discovering Reliable Dependencies from Data: Hardness and Improved Algorithms
The reliable fraction of information is an attractive score for quantify...
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Causal Discovery by Telling Apart Parents and Children
We consider the problem of inferring the directed, causal graph from obs...
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CTRL+Z: Recovering Anonymized Social Graphs
Social graphs derived from online social interactions contain a wealth o...
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Telling Cause from Effect using MDLbased Local and Global Regression
We consider the fundamental problem of inferring the causal direction be...
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Efficiently Discovering Locally Exceptional yet Globally Representative Subgroups
Subgroup discovery is a local pattern mining technique to find interpret...
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Discovering Reliable Approximate Functional Dependencies
Given a database and a target attribute of interest, how can we tell whe...
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Causal Inference by Stochastic Complexity
The algorithmic Markov condition states that the most likely causal dire...
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Causal Inference on Multivariate and MixedType Data
Given data over the joint distribution of two random variables X and Y, ...
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Efficiently Summarising Event Sequences with Rich Interleaving Patterns
Discovering the key structure of a database is one of the main goals of ...
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Identifying Consistent Statements about Numerical Data with DispersionCorrected Subgroup Discovery
Existing algorithms for subgroup discovery with numerical targets do not...
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Keeping it Short and Simple: Summarising Complex Event Sequences with Multivariate Patterns
We study how to obtain concise descriptions of discrete multivariate seq...
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Beauty and Brains: Detecting Anomalous Pattern CoOccurrences
Our world is filled with both beautiful and brainy people, but how often...
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Universal Dependency Analysis
Most data is multidimensional. Discovering whether any subset of dimens...
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Lineartime Detection of Nonlinear Changes in Massively High Dimensional Time Series
Change detection in multivariate time series has applications in many do...
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Flexibly Mining Better Subgroups
In subgroup discovery, also known as supervised pattern mining, discover...
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Canonical Divergence Analysis
We aim to analyze the relation between two random vectors that may poten...
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Jilles Vreeken
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Independent Research Group Leader at Cluster of Excellence MMCI, Saarland University