Multilayer feedforward networks are universal approximators
Neural Networks
Universal approximation using radial-basis-function networks
Neural Computation
Approximation and radial-basis-function networks
Neural Computation
Some new results on neural network approximation
Neural Networks
Machine Learning
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
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ECML '98 Proceedings of the 10th European Conference on Machine Learning
Predicting Time Series with Support Vector Machines
ICANN '97 Proceedings of the 7th International Conference on Artificial Neural Networks
A Note on a Scale-Sensitive Dimension of Linear Bounded Functionals in Banach Spaces
ALT '97 Proceedings of the 8th International Conference on Algorithmic Learning Theory
Supervised Neural Gas with General Similarity Measure
Neural Processing Letters
Feature selection for the SVM: An application to hypertension diagnosis
Expert Systems with Applications: An International Journal
Climate model by SVM based on experienced knowledge in tobacco region division
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Climate prediction by SVM based on initial conditions
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 5
Approximation properties of positive boolean functions
WIRN'05 Proceedings of the 16th Italian conference on Neural Nets
Application of global optimization methods to model and feature selection
Pattern Recognition
Algorithms for discovery of multiple Markov boundaries
The Journal of Machine Learning Research
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This letter presents a sigma-pi-sigma neural network (SPSNN) structure. The SPSNN can learn to implement static mapping that multilayer neural networks and radial basis function networks usually do. The output of the SPSNN has the sum of product-of-sum ...