# Lecture Notes on High Dimensional Linear Regression

arXiv: https://arxiv.org/abs/2412.15633 · HTML: https://mlsanity.com/paper/2412.15633/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- First posted on arXiv 20 Dec 2024.

## Abstract (arXiv)

These lecture notes cover advanced topics in linear regression, with an in-depth exploration of the existence, uniqueness, relations, computation, and non-asymptotic properties of the most prominent estimators in this setting. The covered estimators include least squares, ridgeless, ridge, and lasso. The content follows a proposition-proof structure, making it suitable for students seeking a formal and rigorous understanding of the statistical theory underlying machine learning methods.