We investigate theoretically some properties of variational Bayes approximations based on estimating the mixing coefficients of known densities. We show that, with probability 1 a...
This paper proposes a methodology to generate artificial data sets to evaluate the behavior of machine learning techniques. The methodology relies in the definition of a domain an...
Joaquin Rios-Boutin, Albert Orriols-Puig, Josep Ma...
This paper presents a new approach to automated muscle fiber analysis based on segmenting myofibers with combined region and edge based active contours. It provides reliable and fu...
Thomas Brox, Yoo-Jin Kim, Joachim Weickert, Wolfga...
In this paper, we present e cient algorithms for adjusting con guration parameters of genetic algorithms that operate in a noisy environment. Assuming that the population size is ...
We present an unsupervised algorithm for aligning a pair of shapes in the presence of significant articulated motion and missing data, while assuming no knowledge of a template, u...