We consider the problem of quantizing data generated from disparate sources, e.g. subjects performing actions with different styles, movies with particular genre bias, various con...
Ekaterina Taralova, Fernando DelaTorre, Martial He...
—Traditional clustering algorithms identify just a single clustering of the data. Today’s complex data, however, allow multiple interpretations leading to several valid groupin...
We propose a method based on sparse representation
(SR) to cluster data drawn from multiple low-dimensional
linear or affine subspaces embedded in a high-dimensional
space. Our ...
Nonnegative Matrix Factorization (NMF) has been proven to be effective in text mining. However, since NMF is a well-known unsupervised components analysis technique, the existing ...