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Gradient descent
Gradient descent

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!!! Overview
[{$pagename}] is a first-order iterative optimization [algorithm] for finding the minimum values of a [function].
To find a local minimum of a [function] using [{$pagename}], one takes steps proportional to the negative of the gradient (or of the approximate gradient) of the [function] at the current point. If instead one takes steps proportional to the positive of the gradient, one approaches a local maximum of that function; the procedure is then known as [gradient ascent].
[{$pagename}] is also known as steepest descent. However, [{$pagename}] should not be confused with the method of steepest descent for approximating integrals.
!! More Information
There might be more information for this subject on one of the following:
[{ReferringPagesPlugin before='*' after='\n' }]
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* [#1] - [Gradient_descent|Wikipedia:Gradient_descent|target='_blank'] - based on information obtained 2017-11-29-
This page (revision-1) was last changed on 29-Nov-2024 16:16 by UnknownAuthorTop