Presentation 1993/11/24
A Modified Learning Method for Error Back Propagation Algorithm using the Data of Internal Representation IV : Judgment of local minima using auxiliary output units
Shinji Ishida, Fumio Yoshida, Jin-ichi Matsuda,
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Abstract(in English) In an error back propagation method,the network sometimes fails to complete the learning due to local minima and even if the global minimum can be achieved it takes tremendous learning steps. We have been studying a new learning method,in which auxiliary units are installed in output layer and internal representations are used as the teacher′s signals for them,and we are testing lear ning efficiency of our method through computer simulations. Here,we discuss the attraction effect due to auxiliary output units.It is confirmed that,in our method,we can check whether the net is in the local minima or not during learning phase and improve effectively the learning process.
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Keyword(in English) neural network / error back propagation method / internal representation / learning efficiency / local minimum
Paper # NC93-51
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Committee NC
Conference Date 1993/11/24(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) A Modified Learning Method for Error Back Propagation Algorithm using the Data of Internal Representation IV : Judgment of local minima using auxiliary output units
Sub Title (in English)
Keyword(1) neural network
Keyword(2) error back propagation method
Keyword(3) internal representation
Keyword(4) learning efficiency
Keyword(5) local minimum
1st Author's Name Shinji Ishida
1st Author's Affiliation Nagaoka University of Technology()
2nd Author's Name Fumio Yoshida
2nd Author's Affiliation Nagaoka University of Technology
3rd Author's Name Jin-ichi Matsuda
3rd Author's Affiliation Nagaoka University of Technology
Date 1993/11/24
Paper # NC93-51
Volume (vol) vol.93
Number (no) 341
Page pp.pp.-
#Pages 8
Date of Issue