127 search results - page 12 / 26 » Bayesian Evolutionary Optimization Using Helmholtz Machines |
ICML
2007
IEEE
14 years 10 months ago
2007
IEEE
We present a method for parameter learning in relational Bayesian networks (RBNs). Our approach consists of compiling the RBN model into a computation graph for the likelihood fun...
ICML
2000
IEEE
14 years 2 months ago
2000
IEEE
The reinforcement learning problem can be decomposed into two parallel types of inference: (i) estimating the parameters of a model for the underlying process; (ii) determining be...
GECCO
2008
Springer
13 years 11 months ago
2008
Springer
In this paper we explore the model–building issue of multiobjective optimization estimation of distribution algorithms. We argue that model–building has some characteristics t...
ASC
2006
13 years 10 months ago
2006
For some time, learning Bayesian networks has been both feasible and useful in many problems domains. Recently research has been done on learning equivalence classes of Bayesian n...
GECCO
2009
Springer
14 years 2 months ago
2009
Springer
Typical domains used in machine learning analyses only partially cover the complexity space, remaining a large proportion of problem difficulties that are not tested. Since the ac...