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IJCNN
2006
IEEE
14 years 22 days ago
On derivation of stagewise second-order backpropagation by invariant imbedding for multi-stage neural-network learning
— We present a simple, intuitive argument based on “invariant imbedding” in the spirit of dynamic programming to derive a stagewise second-order backpropagation (BP) algorith...
Eiji Mizutani, Stuart Dreyfus
CCE
2010
13 years 4 months ago
Combined mass and energy integration in process design at the example of membrane-based gas separation systems
This paper presents an approach for combined mass and energy integration in process synthesis and illustrates it at the thermochemical production of crude synthetic natural gas (S...
Martin Gassner, François Maréchal
NIPS
2008
13 years 8 months ago
Non-stationary dynamic Bayesian networks
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Joshua W. Robinson, Alexander J. Hartemink
BMCBI
2007
194views more  BMCBI 2007»
13 years 6 months ago
Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
Xin Zhao, Leo Wang-Kit Cheung
BMCBI
2005
122views more  BMCBI 2005»
13 years 6 months ago
A neural strategy for the inference of SH3 domain-peptide interaction specificity
Background: The SH3 domain family is one of the most representative and widely studied cases of so-called Peptide Recognition Modules (PRM). The polyproline II motif PxxP that gen...
Enrico Ferraro, Allegra Via, Gabriele Ausiello, Ma...