Lecture

Riemannian gradient descent

Description

This lecture covers Riemannian gradient descent, focusing on Taylor expansions, first-order optimality conditions, algorithm templates, line search, sufficient decrease, regularity conditions, and critical points. It also discusses the behavior of local minimizers and the concept of critical points. The instructor explains the pull back of functions through retractions, the definition of local minimizers, and the necessary conditions for a point to be a critical or stationary point. The lecture concludes with a theorem on the sequence produced by Riemannian gradient descent under specific assumptions.

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.

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.