Discovering Faithful `Wickelfeature' Representations in a Connectionist Network

Abstract

A challenging problem for connectionist models is the representation of varying-length sequences (e.g., the sequence of phonemes that compose a word). One representation that has been proposed involves encoding each sequence element with respect to its local context; this is known as a "Wickelfeature" representation. Handcrafted Wickelfeature representations suffer from a number of limitations, as pointed out by Pinker and Prince (1988). However, these limitations can be avoided if the representation is constructed with a priori knowledge of the set of possible sequences. This paper proposes a specialized connectionist network architecture and learning algorithm for the discovery of faithful Wickelfeature representations -- ones that do not lose critical information about the sequence to be encoded. The architecture is applied to a simplified version of Rumelhart and MeClelland's (1986) verb past-tense model.

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Document Details

Document Type
Technical Report
Publication Date
Mar 19, 1990
Accession Number
ADA446057

Entities

People

  • Michael C. Mozer

Organizations

  • University of Colorado Boulder

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DTIC Thesaurus Topics

  • Abstracts
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  • Colorado
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Fields of Study

  • Computer science

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