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Comments on ;Dynamic programming approach to optimal weight selection in multilayer neural networks' [with reply].

B A Pearlmutter¹, P Sanatchandran

¹Dept. of Comput. Sci. and Eng., Oregon Graduate Inst. of Sci. and Technol., Beaverton, OR.

IEEE Transactions on Neural Networks

|January 1, 1992

Summary

This paper clarifies misunderstandings regarding dynamic programming algorithms for feedforward neural networks. It addresses comments on notation and reaffirms the efficiency of the proposed weight-loading method.

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Area of Science:

Computer Science
Artificial Intelligence
Machine Learning

Background:

A previous paper presented an efficient algorithm using dynamic programming for feedforward neural networks.
The algorithm aimed to find weights that load examples with minimal error.

Purpose of the Study:

To address a commenter's claim of a notational contradiction in the original paper.
To clarify misunderstandings regarding the implementation of dynamic programming algorithms in neural network weight loading.

Main Methods:

The study involves a detailed reply to a specific comment on a published algorithm.
The author re-explains the application of dynamic programming principles.

Main Results:

The author asserts that the commenter's concerns stem from a misunderstanding of the algorithm's implementation.
The original paper's methodology for efficient weight loading in neural networks is defended.

Conclusions:

The dynamic programming approach for feedforward neural network weight loading is valid.
Clarification resolves perceived contradictions, reinforcing the algorithm's efficiency.