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AUSAI
2008
Springer
14 years 12 months ago
Using Gaussian Processes to Optimize Expensive Functions
The task of finding the optimum of some function f(x) is commonly accomplished by generating and testing sample solutions iteratively, choosing each new sample x heuristically on t...
Marcus R. Frean, Phillip Boyle
CORR
2010
Springer
209views Education» more  CORR 2010»
14 years 10 months ago
An Algorithm to Extract Rules from Artificial Neural Networks for Medical Diagnosis Problems
Artificial neural networks (ANNs) have been successfully applied to solve a variety of classification and function approximation problems. Although ANNs can generally predict bett...
S. M. Kamruzzaman, Md. Monirul Islam
ESANN
2003
14 years 11 months ago
Neural Networks and M5 model trees in modeling water level-discharge relationship for an Indian river
: In flood management it is important to reliably estimate the discharge in a river. Hydrologists use historic data to establish a rating curve – a relationship between the water...
Biswanath Bhattacharya, Dimitri P. Solomatine
IJCSA
2007
213views more  IJCSA 2007»
14 years 9 months ago
Adaptive Depth Control for Autonomous Underwater Vehicles Based on Feedforward Neural Networks
This paper studies the design and application of the neural network based adaptive control scheme for autonomous underwater vehicle's (AUV's) depth control system that i...
Yang Shi, Weiqi Qian, Weisheng Yan, Jun Li
BMCBI
2010
174views more  BMCBI 2010»
14 years 10 months ago
The effect of prior assumptions over the weights in BayesPI with application to study protein-DNA interactions from ChIP-based h
Background: To further understand the implementation of hyperparameters re-estimation technique in Bayesian hierarchical model, we added two more prior assumptions over the weight...
Junbai Wang