Subspace methods such as PCA, LDA, ICA have become a standard tool to perform visual learning and recognition. In this paper we propose Representational Oriented Component Analysi...
Fernando De la Torre, Ralph Gross, Simon Baker, B....
Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a particular linear combination of the input variables while constraining the numb...
Alexandre d'Aspremont, Francis R. Bach, Laurent El...
One of the main problems in probabilistic grammatical inference consists in inferring a stochastic language, i.e. a probability distribution, in some class of probabilistic models...
Mismatch between training and testing data is a major error source for both Automatic Speech Recognition (ASR) and Automatic Speaker Identification (ASI). In this paper, we first ...
Xi Zhou, Yun Fu, Ming Liu, Mark Hasegawa-Johnson, ...
Motivation: Most previous approaches to model biochemical networks havefocusedeither on the characterization of a networkstructurewith a number of components or on the estimation ...