16 search results - page 1 / 4 » "Ideal Parent" Structure Learning for Continuous V... |
72
Voted
UAI
2004
14 years 11 months ago
2004
In recent years, there is a growing interest in learning Bayesian networks with continuous variables. Learning the structure of such networks is a computationally expensive proced...
77
Voted
NIPS
1997
14 years 11 months ago
1997
We address the problem of learning structure in nonlinear Markov networks with continuous variables. This can be viewed as non-Gaussian multidimensional density estimation exploit...
87
Voted
ICML
1996
IEEE
15 years 10 months ago
1996
IEEE
We introduce a method for learning Bayesian networks that handles the discretization of continuous variables as an integral part of the learning process. The main ingredient in th...
113
Voted
UAI
1998
14 years 11 months ago
1998
In this paper we address the problem of discretization in the context of learning Bayesian networks (BNs) from data containing both continuous and discrete variables. We describe ...
NIPS
1996
14 years 10 months ago
1996
Real-valued random hidden variables can be useful for modelling latent structure that explains correlations among observed variables. I propose a simple unit that adds zero-mean G...