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...
Identifying the patterns of large data sets is a key requirement in data mining. A powerful technique for this purpose is the principal component analysis (PCA). PCA-based clusteri...
The topic of reusable software in robotics is now largely addressed. Components based architectures, where components are independent units that can be reused accross applications,...
We present our joint view for efficient development of efficient and dependable ERTS (Embedded Real-Time Systems). This view is based on the three main viewpoints of (1) the softw...
Bayesian Kullback Ying—Yang dependence reduction system and theory is presented. Via stochastic approximation, implementable algorithms and criteria are given for parameter lear...