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ASME Press Select Proceedings
Intelligent Engineering Systems Through Artificial Neural Networks, Volume 17
Editor
ISBN-10:
0791802655
No. of Pages:
650
Publisher:
ASME Press
Publication date:
2007
eBook Chapter
70 Computation of Gradient and Hessian in Feed-Forward Neural Networks: A Variational Approach
By
S. Lakshmivarahan
,
S. Lakshmivarahan
School Of Computer Science
University Of Oklahoma
Norman, OK 73019
, USA
Search for other works by this author on:
Sudarshan K. Dhall
Sudarshan K. Dhall
School Of Computer Science
University Of Oklahoma
Norman, OK 73019
, USA
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Page Count:
6
-
Published:2007
Citation
Lakshmivarahan, S, & Dhall, SK. "Computation of Gradient and Hessian in Feed-Forward Neural Networks: A Variational Approach." Intelligent Engineering Systems Through Artificial Neural Networks, Volume 17. Ed. Dagli, CH. ASME Press, 2007.
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In this paper we derive explicit expressions for the gradient and the Hessian of the objective function (which in the sum of the squared errors) with respect to the weight matrices in a general feed-forward neural network using the standard methods for computing the first-order and second-order variations of a scalar-valued function of a vector.
Abstract
Introduction
Statement of the Problem
The Variational Approach
Conclusion
References
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