Numerical analysis

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Description

This lecture covers advanced numerical analysis topics such as deep neural networks, optimization methods, and interpolation techniques. The instructor discusses practical applications and theoretical foundations, including KKT conditions and convexity proofs.

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Official source

Ontological neighbourhood

Mathematics

Analysis: Numerical analysis

Related lectures (29)

https://mediaspace.epfl.ch/media/0_8dadggm9

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In course

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Instructor

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Ontological neighbourhood

Mathematics

Analysis: Numerical analysis

Related lectures (29)

Quasi-newton optimization

Covers gradient line search methods and optimization techniques with an emphasis on Wolfe conditions and positive definiteness.

Optimization Methods

Covers optimization methods without constraints, including gradient and line search in the quadratic case.

Optimization Methods

Covers unconstrained and constrained optimization, optimal control, neural networks, and global optimization methods.

Optimization with Constraints

Covers the optimization with constraints and the KKT theorem.

Optimal Control: KKT Conditions

Explores optimal control and KKT conditions for non-linear optimization with constraints.