364 search results - page 5 / 73 » Regularization Learning of Neural Networks for Generalizatio... |
96
Voted
ISCI
1998
14 years 11 months ago
1998
We report new results on the corner classification approach to training feedforward neural networks. It is shown that a prescriptive learning procedure where the weights are simp...
GECCO
2010
Springer
15 years 4 months ago
2010
Springer
HyperNEAT represents a class of neuroevolutionary algorithms that captures some of the power of natural development with a ionally efficient high-level abstraction of development....
VLSISP
2002
14 years 11 months ago
2002
In this paper two agglomerative learning algorithms based on new similarity measures defined for hyperbox fuzzy sets are proposed. They are presented in a context of clustering and...
87
Voted
IJCNN
2006
IEEE
15 years 5 months ago
2006
IEEE
Abstract— Supervised learning rules for spiking neural networks are currently only able to use time-to-first-spike coding and are plagued by very irregular learning curves due t...
65
Voted
ICANN
2007
Springer
15 years 5 months ago
2007
Springer
Abstract. Capturing regularities in high-dimensional data is an important problem in machine learning and signal processing. Here we present a statistical model that learns a nonli...