1261 search results - page 58 / 253 » Improved learning of Bayesian networks |
CEC
2005
IEEE
14 years 1 months ago
2005
IEEE
It is well known that incremental learning can often be difficult for traditional neural network systems, due to newly learned information interfering with previously learned infor...
CORR
2010
Springer
13 years 8 months ago
2010
Springer
Knowing the largest rate at which data can be sent on an end-to-end path such that the egress rate is equal to the ingress rate with high probability can be very practical when ch...
IJAR
2011
12 years 11 months ago
2011
The basic idea of an algebraic approach to learning Bayesian network (BN) structures is to represent every BN structure by a certain uniquely determined vector, called the standar...
ICPR
2004
IEEE
14 years 9 months ago
2004
IEEE
Bidirectional recurrent neural network(BRNN) is a noncausal generalization of recurrent neural network(RNN). It can not learn remote information efficiently due to the problem of ...
BMCBI
2006
13 years 8 months ago
2006
Background: A number of methods that use both protein structural and evolutionary information are available to predict the functional consequences of missense mutations. However, ...