93 search results - page 10 / 19 » Evolving neural networks in compressed weight space |
GECCO
2005
Springer
15 years 3 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...
NIPS
1993
14 years 11 months ago
1993
This paper introduces GNARL, an evolutionary program which induces recurrent neural networks that are structurally unconstrained. In contrast to constructive and destructive algor...
ANNPR
2008
Springer
14 years 11 months ago
2008
Springer
Clustering constitutes an ubiquitous problem when dealing with huge data sets for data compression, visualization, or preprocessing. Prototype-based neural methods such as neural g...
GECCO
2008
Springer
14 years 10 months ago
2008
Springer
This paper presents an study about a new Hybrid method GRASPES - for time series prediction, inspired in F. Takens theorem and based on a multi-start metaheuristic for combinatori...
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IJCINI
2008
14 years 9 months ago
2008
An artificial neural network was trained to classify musical chords into four categories--major, dominant seventh, minor, or diminished seventh--independent of musical key. After ...