Presentation 1994/10/13
Acquisition of Internal Representation using Overload learning - Case Study of Learning Identity-function-
Itsuki Noda,
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Abstract(in English) Acquisition of internal representation by learning identity- functions is important for feature-abstraction.It is,however, difficult to decide the number of hidden units.I apply the overload learning(OLL) technique to overcome this problem.Because OLL causes to reduce the number of effective dimensions of hidden patterns,networks can gets reduced internal representation by learning.Moreover,I show that this technique is useful to get spatial representation from symbolic representation and to integrate various information.
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Keyword(in English) overload learning / internal representation / identity function / feature abstraction / information integration
Paper # NC94-34
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Committee NC
Conference Date 1994/10/13(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Acquisition of Internal Representation using Overload learning - Case Study of Learning Identity-function-
Sub Title (in English)
Keyword(1) overload learning
Keyword(2) internal representation
Keyword(3) identity function
Keyword(4) feature abstraction
Keyword(5) information integration
1st Author's Name Itsuki Noda
1st Author's Affiliation Electro technical Laboratory()
Date 1994/10/13
Paper # NC94-34
Volume (vol) vol.94
Number (no) 272
Page pp.pp.-
#Pages 8
Date of Issue