In this paper we define conditional random fields in reproducing kernel Hilbert spaces and show connections to Gaussian Process classification. More specifically, we prove decompo...
Kernelizing partial least squares (PLS), an algorithm which has been particularly popular in chemometrics, leads to kernel PLS which has several interesting properties, including ...
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...
This paper proposes a new framework to formulate the problem of rushes video summarization as an unsupervised learning problem. We pose the problem of video summarization as one o...
Yang Liu, Feng Zhou, Wei Liu, Fernando De la Torre...
Presentation of the exponential families, of the mixtures of such distributions and how to learn it. We then present algorithms to simplify mixture model, using Kullback-Leibler di...