One of the major weaknesses of current research on the Semantic Web (SW) is the lack of proper means to represent and reason with uncertainty. A number of recent efforts from the ...
Paulo Cesar G. da Costa, Marcelo Ladeira, Rommel N...
In this paper we present a framework for using multi-layer perceptron (MLP) networks in nonlinear generative models trained by variational Bayesian learning. The nonlinearity is h...
Bayesian networks (BNs) provide a means for representing, displaying, and making available in a usable form the knowledge of experts in a given Weld. In this paper, we look at the...
This paper explores the relationship between discourse structure and coverbal gesture. Using the idea of gestural cohesion, we show that coherent topic segments are characterized ...
We present a novel method for approximate inference in Bayesian models and regularized risk functionals. It is based on the propagation of mean and variance derived from the Lapla...
Alexander J. Smola, Vishy Vishwanathan, Eleazar Es...