Directional Clustering Through Matrix Factorization

  • Thomas Blumensath
  • Published 2016 in
    IEEE Transactions on Neural Networks and Learning…

Abstract

This paper deals with a clustering problem where feature vectors are clustered depending on the angle between feature vectors, that is, feature vectors are grouped together if they point roughly in the same direction. This directional distance measure arises in several applications, including document classification and human brain imaging. Using ideas from… (More)
DOI: 10.1109/TNNLS.2015.2505060

Topics

11 Figures and Tables