JMLR
2010
13 years 6 months ago
2010
We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
SAFECOMP
2010
Springer
13 years 9 months ago
2010
Springer
Abstract. Model-based development and automated code generation are increasingly used for actual production code, in particular in mathematical and engineering domains. However, si...
NN
2002
Springer
13 years 11 months ago
2002
Springer
When learning a mixture model, we suffer from the local optima and model structure determination problems. In this paper, we present a method for simultaneously solving these prob...
JMLR
2007
13 years 11 months ago
2007
We introduce standardised building blocks designed to be used with variational Bayesian learning. The blocks include Gaussian variables, summation, multiplication, nonlinearity, a...
JCP
2007
13 years 11 months ago
2007
— This paper proposes a new approach to modelling and controlling Internet end-to-end loss behaviours. Rather than select the model structure from the loss observations as being ...
NIPS
1998
14 years 24 days ago
1998
When learning a mixture model, we suffer from the local optima and model structure determination problems. In this paper, we present a method for simultaneously solving these prob...
ICMCS
2008
IEEE
14 years 5 months ago
2008
IEEE
Several stochastic models provide an effective framework to identify the temporal structure of audiovisual data. Most of them need as input a first video structure, i.e. connecti...
ICML
2007
IEEE
15 years 8 days ago
2007
IEEE
We propose a class of graphical models appropriate for structure prediction problems where the model structure is a function of the output structure. Incremental Sigmoid Belief Ne...