The goal of a Boolean matrix decomposition (BMD) is to represent a given Boolean matrix as a product of two or more Boolean factor matrices. It is a well-known and researched problem with a wide range of applications, e.g. in multi-label classification, clustering, bioinformatics, or pattern mining. In this project, we aim to work on a recently published algorithm (XBMaD) and design and implement approaches to improve the general performance of the algorithm. Additionally, we will evaluate the performance on a range of practical applications.

Duration and Type

  • Preferable 1 semester, but can be also done in 2 semesters
  • Honours project, other postgraduate project (MSc, MProfStuds, …)


  • Basic maths, CS, and machine learning skills
  • Programming in Java or Python

Supervisor and contact

  • Joerg Wicker
  • Send CV and transcript by mail to Joerg Wicker