200 search results - page 11 / 40 » On the Consistency of Discrete Bayesian Learning |
ICML
2010
IEEE
13 years 6 months ago
2010
IEEE
Classical dynamic Bayesian networks (DBNs) are based on the homogeneous Markov assumption and cannot deal with heterogeneity and non-stationarity in temporal processes. Various ap...
IJAR
2006
13 years 7 months ago
2006
We consider the problem of learning the parameters of a Bayesian network from data, while taking into account prior knowledge about the signs of influences between variables. Such...
JMLR
2006
13 years 7 months ago
2006
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
UAI
2001
13 years 9 months ago
2001
This paper presents a new deterministic approximation technique in Bayesian networks. This method, "Expectation Propagation," unifies two previous techniques: assumed-de...
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...