A large number of learning algorithms, for example, spectral clustering, kernel Principal Components Analysis and many manifold methods are based on estimating eigenvalues and eig...
In this paper, we consider facial expression recognition using an unsupervised learning framework. Specifically, given a data set composed of a number of facial images of the same...
Behnood Gholami, Wassim M. Haddad, Allen Tannenbau...
We present a method to extract principal deformation modes from a set of articulated models describing the human spine. The spine was expressed as a set of rigid transforms that su...
Jonathan Boisvert, Xavier Pennec, Hubert Labelle, ...
In this paper, we address the pre-image problem in kernel principal component analysis (KPCA). The preimage problem finds a pattern as the pre-image of a feature vector defined in...
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...