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07/14/2023
Efficiently Factorizing Boolean Matrices using Proximal Gradient Descent
Addressing the interpretability problem of NMF on Boolean data, Boolean ...
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01/31/2023
Preserving local densities in low-dimensional embeddings
Low-dimensional embeddings and visualizations are an indispensable tool ...
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06/16/2022
All the World's a (Hyper)Graph: A Data Drama
We introduce Hyperbard, a dataset of diverse relational data representat...
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12/16/2021
Differentially Describing Groups of Graphs
How does neural connectivity in autistic children differ from neural con...
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10/18/2021
Label-Descriptive Patterns and their Application to Characterizing Classification Errors
State-of-the-art deep learning methods achieve human-like performance on...
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05/29/2021
Graph Similarity Description: How Are These Graphs Similar?
How do social networks differ across platforms? How do information netwo...
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05/05/2021
Formally Justifying MDL-based Inference of Cause and Effect
The algorithmic independence of conditionals, which postulates that the ...
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03/02/2021
Factoring out prior knowledge from low-dimensional embeddings
Low-dimensional embedding techniques such as tSNE and UMAP allow visuali...
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09/06/2020
Discovering Reliable Causal Rules
We study the problem of deriving policies, or rules, that when enacted o...
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03/23/2020
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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08/30/2019
Discovering Reliable Correlations in Categorical Data
In many scientific tasks we are interested in discovering whether there ...
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04/25/2019
Summarizing Data Succinctly with the Most Informative Itemsets
Knowledge discovery from data is an inherently iterative process. That i...
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04/25/2019
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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03/12/2019
Testing Conditional Independence on Discrete Data using Stochastic Complexity
Testing for conditional independence is a core aspect of constraint-base...
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02/18/2019
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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02/18/2019
Comparing Apples and Oranges: Measuring Differences between Data Mining Results
Deciding whether the results of two different mining algorithms provide ...
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02/07/2019
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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02/07/2019
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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02/06/2019
Finding Good Itemsets by Packing Data
The problem of selecting small groups of itemsets that represent the dat...
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01/21/2019
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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09/14/2018
Discovering Reliable Dependencies from Data: Hardness and Improved Algorithms
The reliable fraction of information is an attractive score for quantify...
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08/20/2018
Causal Discovery by Telling Apart Parents and Children
We consider the problem of inferring the directed, causal graph from obs...
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11/15/2017
CTRL+Z: Recovering Anonymized Social Graphs
Social graphs derived from online social interactions contain a wealth o...
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09/26/2017
Telling Cause from Effect using MDL-based Local and Global Regression
We consider the fundamental problem of inferring the causal direction be...
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09/22/2017
Efficiently Discovering Locally Exceptional yet Globally Representative Subgroups
Subgroup discovery is a local pattern mining technique to find interpret...
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05/25/2017
Discovering Reliable Approximate Functional Dependencies
Given a database and a target attribute of interest, how can we tell whe...
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02/22/2017
Causal Inference by Stochastic Complexity
The algorithmic Markov condition states that the most likely causal dire...
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02/21/2017
Causal Inference on Multivariate and Mixed-Type Data
Given data over the joint distribution of two random variables X and Y, ...
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01/27/2017
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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01/26/2017
Identifying Consistent Statements about Numerical Data with Dispersion-Corrected Subgroup Discovery
Existing algorithms for subgroup discovery with numerical targets do not...
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12/22/2015
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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12/22/2015
Beauty and Brains: Detecting Anomalous Pattern Co-Occurrences
Our world is filled with both beautiful and brainy people, but how often...
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10/28/2015
Universal Dependency Analysis
Most data is multi-dimensional. Discovering whether any subset of dimens...
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10/28/2015
Linear-time Detection of Non-linear Changes in Massively High Dimensional Time Series
Change detection in multivariate time series has applications in many do...
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10/28/2015
Flexibly Mining Better Subgroups
In subgroup discovery, also known as supervised pattern mining, discover...
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10/28/2015
