ICANN
2001
Springer
13 years 9 months ago
2001
Springer
In many practical engineering design problems, the form of objective function is not given explicitly in terms of design variables. Given the value of design variables, under this ...
ICANN
2001
Springer
13 years 9 months ago
2001
Springer
This paper proposes an on-line error detecting method for a manually annotated corpus using min-max modular (M3 ) neural networks. The basic idea of the method is to use guaranteed...
ICANN
2001
Springer
13 years 9 months ago
2001
Springer
Humans tend to group together related properties in order to understand complex phenomena. When modeling large problems with limited representational resources, it is important to...
ICANN
2001
Springer
13 years 9 months ago
2001
Springer
Unlike traditional reinforcement learning (RL), market-based RL is in principle applicable to worlds described by partially observable Markov Decision Processes (POMDPs), where an ...
ICANN
2001
Springer
13 years 9 months ago
2001
Springer
In manipulating data such as in supervised learning, we often extract new features from original features for the purpose of reducing the dimensions of feature space and achieving ...
ICANN
2001
Springer
13 years 9 months ago
2001
Springer
ICANN
2001
Springer
13 years 9 months ago
2001
Springer
Natural videos obtained from a camera mounted on a cat’s head are used as stimuli for a network of subspace energy detectors. The network is trained by gradient ascent on an obje...
ICANN
2001
Springer
13 years 9 months ago
2001
Springer
We introduce a simple asset pricing model with two types of adaptively learning traders, fundamentalists and technical traders. Traders update their beliefs according to past perfo...
ICANN
2001
Springer
13 years 9 months ago
2001
Springer
ICANN
2001
Springer
2001
Springer
Learning and Prediction of the Nonlinear Dynamics of Biological Neurons with Support Vector Machines
13 years 9 months ago
Based on biological data we examine the ability of Support Vector Machines (SVMs) with gaussian kernels to learn and predict the nonlinear dynamics of single biological neurons. We...