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NN
1998
Springer
14 years 11 months ago
1998
Springer
Learning long-term temporal dependencies with recurrent neural networks can be a difficult problem. It has recently been shown that a class of recurrent neural networks called NA...
IROS
2006
IEEE
15 years 6 months ago
2006
IEEE
— Humanoid robots are routinely engaged in tasks requiring the coordination between multiple degrees of freedom and sensory inputs, often achieved through the use of sensorymotor...
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CIMCA
2005
IEEE
15 years 5 months ago
2005
IEEE
An efficient training method for block-diagonal recurrent neural networks is proposed. The method modifies the RPROP algorithm, originally developed for static models, in order to...
ICONIP
2004
15 years 1 months ago
2004
Abstract. This paper presents a neural-evolutionary framework for the simulation of market models in a bounded rationality scenario. Each agent involved in the scenario make use of...
CORR
2010
Springer
14 years 12 months ago
2010
Springer
We tackle the fundamental problem of Bayesian active learning with noise, where we need to adaptively select from a number of expensive tests in order to identify an unknown hypot...