A maximum-entropy approach to generative similarity-based classifiers model is proposed. First, a descriptive set of similarity statistics is assumed to be sufficient for classifi...
Feature set partitioning generalizes the task of feature selection by partitioning the feature set into subsets of features that are collectively useful, rather than by finding a ...
We describe Nonnegative Double Singular Value Decomposition (NNDSVD), a new method designed to enhance the initialization stage of nonnegative matrix factorization (NMF). NNDSVD c...
Spectral clustering and path-based clustering are two recently developed clustering approaches that have delivered impressive results in a number of challenging clustering tasks. ...
We have developed an informative sample subspace (ISS) method that is suitable for projecting high-dimensional data onto a low-dimensional subspace for classification purposes. In...