Nonnegative matrix factorization (NMF) has been shown to be an efficient clustering tool. However, NMF`s batch nature necessitates recomputation of whole basis set for new samples...
This communication deals with data reduction and regression. A set of high dimensional data (e.g., images) usually has only a few degrees of freedom with corresponding variables t...
Matthieu Brucher, Christian Heinrich, Fabrice Heit...
The attribute selection techniques for supervised learning, used in the preprocessing phase to emphasize the most relevant attributes, allow making models of classification simple...
We show that the relevant information of a supervised learning problem is contained up to negligible error in a finite number of leading kernel PCA components if the kernel matche...
Mikio L. Braun, Joachim M. Buhmann, Klaus-Robert M...
Abstract. We propose a novel unsupervised transfer learning framework that utilises unlabelled auxiliary data to quantify and select the most relevant transferrable knowledge for r...