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Language Learning in Massively-parallel Networks by Terrence J. Sejnowski is a scholarly article available to read on EtoBox.

What is Language Learning in Massively-parallel Networks about?

Massively-parallel connectionist networks have traditionally been applied to constraint-satisfaction in early visual processing (Ballard, Hinton & Sejnowski, 1983), but are now being applied to problems ranging from the Traveling-Salesman Problem to language acquisition (Rumelhart & MeClelland, 1986). In these networks, knowledge is represented by the distributed pattern of activity in a large number of relatively simple neuron-like processing units, and computation is performed in parallel by the use of connections between the units.

Author

Terrence J. Sejnowski

Published

1986

Language

EN