Data Structures and Algorithms

    

Some Optimization Methods that Use a Limited Number of Second Derivatives

Authors: Stephen P. Smith

This paper describes two optimization methods that use all first derivatives, and a subset of second derivatives, all of which are available with backward differentiation. The first method is Newton’s method on a direction set that changes dynamically during iteration. The second method is a quasi-Newton method that approximates the inverse Hessian matrix using a subset of second derivatives.

Comments: 5 Pages.

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Submission history

[v1] 2021-03-13 23:48:31

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