Gaussian process classifiers (GPCs) are Bayesian probabilistic kernel classifiers. In GPCs, the probability of belonging to a certain class at an input location is monotonically re...
—Considering process variability at the behavior synthesis level is necessary, because it makes some instances of function units slower and others faster, resulting in unbalanced...
This paper presents a novel motion segmentation algorithm on the basis of mixture of Dirichlet process (MDP) models, a kind of nonparametric Bayesian framework. In contrast to pre...
Security, privacy and governance are increasingly the focus of government regulations in the U.S., Europe and elsewhere. This trend has created a “regulation compliance” probl...
Nadzeya Kiyavitskaya, Nicola Zeni, Travis D. Breau...
Most of today’s distributed computing systems in the field do not support the migration of execution entities among computing nodes during runtime. The relatively static associa...