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NIPS
2000
15 years 9 months ago
Learning Continuous Distributions: Simulations With Field Theoretic Priors
Learning of a smooth but nonparametric probability density can be regularized using methods of Quantum Field Theory. We implement a field theoretic prior numerically, test its eff...
Ilya Nemenman, William Bialek
NIPS
1989
15 years 8 months ago
The Cascade-Correlation Learning Architecture
Cascade-Correlation is a new architecture and supervised learning algorithm for artificial neural networks. Instead of just adjusting the weights in a network of fixed topology,...
Scott E. Fahlman, Christian Lebiere
JIB
2006
220views more  JIB 2006»
15 years 7 months ago
An assessment of machine and statistical learning approaches to inferring networks of protein-protein interactions
Protein-protein interactions (PPI) play a key role in many biological systems. Over the past few years, an explosion in availability of functional biological data obtained from hi...
Fiona Browne, Haiying Wang, Huiru Zheng, Francisco...
IJON
2007
184views more  IJON 2007»
15 years 7 months ago
Convex incremental extreme learning machine
Unlike the conventional neural network theories and implementations, Huang et al. [Universal approximation using incremental constructive feedforward networks with random hidden n...
Guang-Bin Huang, Lei Chen
BMCBI
2004
140views more  BMCBI 2004»
15 years 7 months ago
What can we learn from noncoding regions of similarity between genomes?
Background: In addition to known protein-coding genes, large amounts of apparently non-coding sequence are conserved between the human and mouse genomes. It seems reasonable to as...
Thomas A. Down, Tim J. P. Hubbard