Lecture

Filter and Graph Learning with Optimal Transport

Description

This lecture presents FIGLearn, a method for learning filters and graphs using optimal transport. It covers the signal generation model, the approach to minimize Wasserstein distance, the algorithm involving filter and graph learning steps, limitations in non-convex optimization, an application in missing data inference, and a summary highlighting the flexibility and performance of the approach.

Official source

https://mediaspace.epfl.ch/media/0_jll45xl6

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

Information engineering

Machine learning: Artificial neural networks

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.