Lecture

Convex Optimization: Gradient Algorithms

In course

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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.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_yzltg2ay

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Ontological neighbourhood

Mathematics

Algebra: Linear algebra

Statistics

Data analysis: Regression analysis

Theoretical computer science

Algorithms and data structures: Combinatorial optimization

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