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» Validation of protein models by a neural network approach
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JISE
2007
43views more  JISE 2007»
13 years 7 months ago
A Tableless Approach for High-Level Power Modeling Using Neural Networks
Chih-Yang Hsu, Wen-Tsan Hsieh, Chien-Nan Jimmy Liu...
BIBM
2008
IEEE
172views Bioinformatics» more  BIBM 2008»
14 years 2 months ago
Boosting Methods for Protein Fold Recognition: An Empirical Comparison
Protein fold recognition is the prediction of protein’s tertiary structure (Fold) given the protein’s sequence without relying on sequence similarity. Using machine learning t...
Yazhene Krishnaraj, Chandan K. Reddy
NN
2007
Springer
13 years 7 months ago
Edge of chaos and prediction of computational performance for neural circuit models
We analyze in this article the significance of the edge of chaos for real-time computations in neural microcircuit models consisting of spiking neurons and dynamic synapses. We ...
Robert A. Legenstein, Wolfgang Maass
EAAI
2006
98views more  EAAI 2006»
13 years 7 months ago
Neural network-based failure rate prediction for De Havilland Dash-8 tires
An artificial neural network (ANN) model for predicting the failure rate of De Havilland Dash-8 airplane tires utilizing the twolayered feed-forward back-propagation algorithm as ...
Ahmed Z. Al-Garni, Ahmad Jamal, Abid M. Ahmad, Abd...
IJCNN
2006
IEEE
14 years 1 months ago
Model Selection via Bilevel Optimization
— A key step in many statistical learning methods used in machine learning involves solving a convex optimization problem containing one or more hyper-parameters that must be sel...
Kristin P. Bennett, Jing Hu, Xiaoyun Ji, Gautam Ku...