32 search results - page 5 / 7 » Discretizing Continuous Attributes While Learning Bayesian N... |
ALGORITHMICA
2006
13 years 7 months ago
2006
Abstract. In this paper we present a coarse-grained parallel algorithm, CONQUEST, for constructing boundederror summaries of high-dimensional binary attributed data in a distribute...
KDD
2002
ACM
14 years 8 months ago
2002
ACM
In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...
SASO
2009
IEEE
14 years 2 months ago
2009
IEEE
An optimal sensor layout is attained when a limited number of sensors are placed in an area such that the cost of the placement is minimised while the value of the obtained inform...
NIPS
2008
13 years 9 months ago
2008
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
JMLR
2010
13 years 2 months ago
2010
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...