140 search results - page 7 / 28 » Perspectives and challenges for recurrent neural network tra... |
IROS
2007
IEEE
14 years 2 months ago
2007
IEEE
- We present a connectionist model that combines motions and language based on the behavioral experiences of a real robot. Two models of recurrent neural network with parametric bi...
GECCO
2005
Springer
14 years 1 months ago
2005
Springer
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
GECCO
2004
Springer
14 years 1 months ago
2004
Springer
Spiking neural networks are computationally more powerful than conventional artificial neural networks. Although this fact should make them especially desirable for use in evoluti...
ICASSP
2011
IEEE
12 years 11 months ago
2011
IEEE
We present several modifications of the original recurrent neural network language model (RNN LM). While this model has been shown to significantly outperform many competitive l...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
Many real-world sequence learning tasks require the prediction of sequences of labels from noisy, unsegmented input data. In speech recognition, for example, an acoustic signal is...