DocumentCode :
1186489
Title :
Spurious Valleys in the Error Surface of Recurrent Networks—Analysis and Avoidance
Author :
Horn, Jason ; De Jesús, Orlando ; Hagan, Martin T.
Author_Institution :
Agilent Technol., High Freq. Technol. Center, Santa Clara, CA
Volume :
20
Issue :
4
fYear :
2009
fDate :
4/1/2009 12:00:00 AM
Firstpage :
686
Lastpage :
700
Abstract :
This paper gives a detailed analysis of the error surfaces of certain recurrent networks and explains some difficulties encountered in training recurrent networks. We show that these error surfaces contain many spurious valleys, and we analyze the mechanisms that cause the valleys to appear. We demonstrate that the principle mechanism can be understood through the analysis of the roots of random polynomials. This paper also provides suggestions for improvements in batch training procedures that can help avoid the difficulties caused by spurious valleys, thereby improving training speed and reliability.
Keywords :
backpropagation; error statistics; learning (artificial intelligence); recurrent neural nets; backpropagation; error surface; neural networks; random polynomial; recurrent network training; reliability; spurious valley; training speed; Backpropagation; error surface; recurrent neural networks; spurious minima; spurious valleys; training; Algorithms; Artificial Intelligence; Computer Simulation; Neural Networks (Computer); Nonlinear Dynamics;
fLanguage :
English
Journal_Title :
Neural Networks, IEEE Transactions on
Publisher :
ieee
ISSN :
1045-9227
Type :
jour
DOI :
10.1109/TNN.2008.2012257
Filename :
4798196
Link To Document :
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