704 search results - page 6 / 141 » Improved Learning of AC0 Functions |
ESANN
2003
13 years 9 months ago
2003
In this paper a neural network for approximating function is described. The activation functions of the hidden nodes are the Radial Basis Functions (RBF) whose parameters are learn...
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
Basis functions derived from an undirected graph connecting nearby samples from a Markov decision process (MDP) have proven useful for approximating value functions. The success o...
GECCO
2006
Springer
13 years 11 months ago
2006
Springer
Genetic Programming offers freedom in the definition of the cost function that is unparalleled among supervised learning algorithms. However, this freedom goes largely unexploited...
ITS
2004
Springer
14 years 26 days ago
2004
Springer
Abstract. Successful learning though exploration in open learning environments has been shown to depend on whether students possess the necessary meta-cognitive skills, including s...
FOCI
2007
IEEE
14 years 1 months ago
2007
IEEE
— Backpropagation through time is a very popular discrete-time recurrent neural network training algorithm. However, the computational time associated with the learning process t...