In this work a new adaptive fast variational sparse Bayesian learning (V-SBL) algorithm is proposed that is a variational counterpart of the fast marginal likelihood maximization ...
Dmitriy Shutin, Thomas Buchgraber, Sanjeev R. Kulk...
A central problem in the analysis of motion capture (Mo-
Cap) data is how to decompose motion sequences into primitives.
Ideally, a description in terms of primitives should
fac...
—Large scale production grids are a major case for autonomic computing. Following the classical definition of Kephart, an autonomic computing system should optimize its own beha...
This paper shows how linguistic classification knowledge can be extracted from numerical data for pattern classification problems with many continuous attributes by genetic algori...
In this paper we present an innovative prototype Open Source Teaching/Learning Collaboratory created at UC Merced that will provide the foundation for offering the vast majority of...
Jeff Wright, Stefano Carpin, Alberto Cerpa, German...