Analysis of the Minimum-Norm Least-Squares Estimator and Its Double-Descent Behavior

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.

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.