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» Multilayer neural networks and Bayes decision theory
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IJCNN
2000
IEEE
13 years 12 months ago
On Derivation of MLP Backpropagation from the Kelley-Bryson Optimal-Control Gradient Formula and Its Application
The well-known backpropagation (BP) derivative computation process for multilayer perceptrons (MLP) learning can be viewed as a simplified version of the Kelley-Bryson gradient f...
Eiji Mizutani, Stuart E. Dreyfus, Kenichi Nishio
FOCI
2007
IEEE
14 years 1 months ago
Almost All Learning Machines are Singular
— A learning machine is called singular if its Fisher information matrix is singular. Almost all learning machines used in information processing are singular, for example, layer...
Sumio Watanabe
TNN
2010
234views Management» more  TNN 2010»
13 years 2 months ago
Novel maximum-margin training algorithms for supervised neural networks
This paper proposes three novel training methods, two of them based on the back-propagation approach and a third one based on information theory for Multilayer Perceptron (MLP) bin...
Oswaldo Ludwig, Urbano Nunes
WSC
2004
13 years 9 months ago
A Near Optimal Approach to Quality of Service Data Replication Scheduling
This paper describes an approach to real-time decisionmaking for quality of service based scheduling of distributed asynchronous data replication. The proposed approach addresses ...
Kevin Adams, Denis Gracanin, Dusan Teodorovic
CORR
2010
Springer
104views Education» more  CORR 2010»
13 years 7 months ago
Empirical learning aided by weak domain knowledge in the form of feature importance
Standard hybrid learners that use domain knowledge require stronger knowledge that is hard and expensive to acquire. However, weaker domain knowledge can benefit from prior knowle...
Ridwan Al Iqbal