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Lecture
Convex Optimization: Gradient Algorithms
Description
This lecture covers convex optimization problems, the steepest descent algorithm, the Newton method, and the conjugate gradient method. It explains how to find the global minimum of a convex function using gradient-based algorithms and discusses strategies to improve convergence.
Official source
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