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ESANN
2007

Systematicity in sentence processing with a recursive self-organizing neural network

8 years 10 months ago
Systematicity in sentence processing with a recursive self-organizing neural network
Abstract. As potential candidates for human cognition, connectionist models of sentence processing must learn to behave systematically by generalizing from a small traning set. It was recently shown that Elman networks and, to a greater extent, echo state networks (ESN) possess limited ability to generalize in artificial language learning tasks. We study this capacity for the recently introduced recursive self-organizing neural network model and show that its performance is comparable with ESNs.
Igor Farkas, Matthew W. Crocker
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2007
Where ESANN
Authors Igor Farkas, Matthew W. Crocker
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