Lecture

The Hessian and Newton's method

In course

Sit sint excepteur id commodo ea laborum dolore exercitation sunt deserunt. Adipisicing ullamco ad velit sunt quis. Consectetur ea dolore officia ut commodo proident excepteur duis anim do nostrud deserunt consectetur nisi. Nostrud deserunt irure aute laboris nostrud in occaecat aute commodo sint aliqua elit est. Magna cillum aliqua reprehenderit nostrud culpa minim proident commodo velit qui ad duis. Ex esse quis ipsum laboris laboris velit ullamco aliquip consectetur aute.

Description

This lecture covers the concept of the Hessian, a linear operator, and its application in Newton's method for optimization. The Hessian is a symmetric linear map with real eigenvalues. Newton's method aims to solve equations of the form f(x) = 0 using iterative processes. The lecture also discusses Lipschitz continuity of Hessians and the local convergence rate of Newton's method.

Instructor

labore deserunt

Sit magna sunt officia ut. Deserunt cupidatat quis mollit laboris consequat sint duis excepteur nulla officia pariatur. Incididunt Lorem elit ut eiusmod veniam voluptate Lorem id labore occaecat velit.

Official source

https://mediaspace.epfl.ch/media/0_scwwo5t1

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Ontological neighbourhood

Mathematics

Analysis: Functional analysis, Calculus

Algebra: Linear algebra

Related lectures (43)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.