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NIPS
1997
15 years 7 months ago
Learning Generative Models with the Up-Propagation Algorithm
Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
Jong-Hoon Oh, H. Sebastian Seung
CASCON
1996
77views Education» more  CASCON 1996»
15 years 7 months ago
Harvesting design for an application framework
Framework design begins with domain analysis. Either the problem domain is analyzed to create a new design, or the solution domain is analyzed to understand how the problem has al...
Joan Boone
CEC
2010
IEEE
15 years 7 months ago
Learning-assisted evolutionary search for scalable function optimization: LEM(ID3)
Inspired originally by the Learnable Evolution Model(LEM) [5], we investigate LEM(ID3), a hybrid of evolutionary search with ID3 decision tree learning. LEM(ID3) involves interleav...
Guleng Sheri, David Corne
BMCBI
2010
161views more  BMCBI 2010»
15 years 6 months ago
GeneMesh: a web-based microarray analysis tool for relating differentially expressed genes to MeSH terms
Background: An important objective of DNA microarray-based gene expression experimentation is determining interrelationships that exist between differentially expressed genes and ...
Saurin D. Jani, Gary L. Argraves, Jeremy L. Barth,...
BMCBI
2010
123views more  BMCBI 2010»
15 years 6 months ago
An improved classification of G-protein-coupled receptors using sequence-derived features
Background: G-protein-coupled receptors (GPCRs) play a key role in diverse physiological processes and are the targets of almost two-thirds of the marketed drugs. The 3 D structur...
Zhen-Ling Peng, Jian-Yi Yang, Xin Chen