Descent Methods and Newton Method with Line Search
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Description
This lecture covers the comparison between descent methods and Newton's method, including modifications for positive definite cases, line search algorithm application, and iterations analysis showing convergence towards the minimum point.
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Covers the concept of gradient descent in scalar cases, focusing on finding the minimum of a function by iteratively moving in the direction of the negative gradient.
