Newton's method | Wolfe Condition | Theory and Python Code | Optimization Algorithms #3

In this one, I will show you what the (damped) newton algorithm is and how to use it with the Wolfe condition for backtracking. We will approach both methods from intuitive and animated perspectives. Next, let’s talk about the line search we are going to use in this tutorial, which is based on Wolfe criterion. This is achieved by the Wolfe condition, which sufficiently decreases our function ! The Wolfe condition combines both the Armijo condition as well as an additional curvature condition to formulate the strong Wolfe condition. The curvature condition ensures a sufficient increase of the gradient. This is also a strong wolfe condition, which restricts slopes from getting too positive, hence excluding points far away from stationary points.

⏲Outline⏲

00:00 Introduction
00:57 (Damped) Newton Method
03:27 Wolfe Criterion
04:44 Python Implementation
17:55 Animation Module
32:42 Animating Iterations
35:57 Outro

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#python #optimization #algorithm

[Bozbeybey]

Thank you sir. Such a clear explanation. It is like a diamond. So smooth so beautiful.

[TheScienceSpectrum]

Ahmad is the most underrated professor i have ever seen.

[bangalisohojranna]

Thank you for the geometric description. very helpful

[siyammali]

Registered successfully...Glad to view valuable sessions in such a conference

[hacglavuz]

god i am so glad you labeled stuff like step size and direction, my teacher didnt and all it did was waste like 30 mins of my time

[قناةالبقميللقرانالكريم]

Thank you for this amazing lecture Sir.

[ThreedudesMeenakshy]

Great lecture sir, thanks for providing it for free

[headball]

Great explanation! Thanks to you I finally understood it!

[alextroy]

Thank you sir this tutorial was very helpful! :)

[bigarm]

Excellent lecture! Thank you for making it public!

[lofaze]

sir kindly add one problem solution explaination so that theory concept will be clear to us very easy .

[maelynbaylon]

Simple and to the point lecture.. Thank you professor.

[reshmaninawe]

Kindly upload more lectures of programming in physics

[KanalABCAzerbaijan]

Sir plz tell me aapne konsi book follow ki h...?

[siyahoyuncu]

If dk = -gradient( f(xk)) ( direction of steepest descent method), so (gradient of f at xk)_T dk = -| gradient of f at xk| ^2

[EarningStuff]

Any website to understand Armijo rule better?

[itsgachawolf]

Hello sir can u provide the python code?

[muhammetnacakc]

very bad explaination iam not able to understand a sinle bit