Sciweavers

254 search results - page 22 / 51
» Combining Bayesian Networks with Higher-Order Data Represent...
Sort
View
UAI
2003
14 years 10 months ago
Large-Sample Learning of Bayesian Networks is NP-Hard
In this paper, we provide new complexity results for algorithms that learn discrete-variable Bayesian networks from data. Our results apply whenever the learning algorithm uses a ...
David Maxwell Chickering, Christopher Meek, David ...
ECAI
2010
Springer
14 years 10 months ago
Using Bayesian Networks in an Industrial Setting: Making Printing Systems Adaptive
Abstract. Control engineering is a field of major industrial importance as it offers principles for engineering controllable physical devices, such as cell phones, television sets,...
Arjen Hommersom, Peter J. F. Lucas
CIDM
2009
IEEE
15 years 4 months ago
A new hybrid method for Bayesian network learning With dependency constraints
Abstract— A Bayes net has qualitative and quantitative aspects: The qualitative aspect is its graphical structure that corresponds to correlations among the variables in the Baye...
Oliver Schulte, Gustavo Frigo, Russell Greiner, We...
KDD
2000
ACM
153views Data Mining» more  KDD 2000»
15 years 1 months ago
The generalized Bayesian committee machine
In this paper we introduce the Generalized Bayesian Committee Machine (GBCM) for applications with large data sets. In particular, the GBCM can be used in the context of kernel ba...
Volker Tresp
UAI
2003
14 years 10 months ago
Bayesian Hierarchical Mixtures of Experts
The Hierarchical Mixture of Experts (HME) is a well-known tree-structured model for regression and classification, based on soft probabilistic splits of the input space. In its o...
Christopher M. Bishop, Markus Svensén