Self-Organizing Features and Categories Through Attentive Resonance
OA Version
Citation
Abstract
Because "people create features to subserve the representation and categorization of objects" (p. 3), the authors "provide an account of feature learning in which the components of a representation have close ties to the categorization history of the organism" (p. 5). This commentary surveys self-organizing neural models that clarify this process. These models suggest how "top-down information should constrain the search for relevant dimensions/features of categorization" (p. 23).
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Copyright 1999 Boston University. Permission to copy without fee all or part of this material is granted provided that: 1. The copies are not made or distributed for direct commercial advantage; 2. the report title, author, document number, and release date appear, and notice is given that copying is by permission of BOSTON UNIVERSITY TRUSTEES. To copy otherwise, or to republish, requires a fee and / or special permission.