Loading [a11y]/accessibility-menu.js
Analysis of the Minimum-Norm Least-Squares Estimator and Its Double-Descent Behavior [Lecture Notes] | IEEE Journals & Magazine | IEEE Xplore
Scheduled Maintenance: On Tuesday, 25 February, IEEE Xplore will undergo scheduled maintenance from 1:00-5:00 PM ET (1800-2200 UTC). During this time, there may be intermittent impact on performance. We apologize for any inconvenience.

Analysis of the Minimum-Norm Least-Squares Estimator and Its Double-Descent Behavior [Lecture Notes]


Abstract:

Linear regression models have a wide range of applications in statistics, signal processing, and machine learning. In this Lecture Notes column we will examine the perfor...Show More

Abstract:

Linear regression models have a wide range of applications in statistics, signal processing, and machine learning. In this Lecture Notes column we will examine the performance of the least-squares (LS) estimator with a focus on the case when there are more parameters than training samples, which is often overlooked in textbooks on estimation.
Published in: IEEE Signal Processing Magazine ( Volume: 40, Issue: 3, May 2023)
Page(s): 39 - 75
Date of Publication: 01 May 2023

ISSN Information:

Funding Agency:


References

References is not available for this document.