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» A Connectionist Architecture for Learning to Parse
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AMAI
1999
Springer
14 years 9 months ago
Pattern recognition by an optical thin-film multilayer model
This paper describes a computational learning model inspired by the technology of optical thin-film multilayers from the field of optics. With the thicknesses of thin-film layers ...
Xiaodong Li, Martin K. Purvis
IJCNN
2006
IEEE
15 years 3 months ago
Knowledge Representation and Possible Worlds for Neural Networks
— The semantics of neural networks can be analyzed mathematically as a distributed system of knowledge and as systems of possible worlds expressed in the knowledge. Learning in a...
Michael J. Healy, Thomas P. Caudell
COLING
1996
14 years 11 months ago
FeasPar - A Feature Structure Parser Learning to Parse Spoken Language
We describe and experimentally evaluate a system, FeasPar, that learns parsing spontaneous speech. To train and run FeasPar (Feature Structure Parser), only limited handmodeled kn...
Finn Dag Buø, Alex Waibel
AAAI
2007
14 years 12 months ago
The Marchitecture: A Cognitive Architecture for a Robot Baby
The Marchitecture is a cognitive architecture for autonomous development of representations. The goals of The Marchitecture are domain independence, operating in the absence of kn...
Marc Pickett, Tim Oates
MICAI
2004
Springer
15 years 2 months ago
A Biologically Motivated and Computationally Efficient Natural Language Processor
Abstract. Conventional artificial neural network models lack many physiological properties of the neuron. Current learning algorithms are more concerned to computational performanc...
João Luís Garcia Rosa