---
title: "Machine Learning Blog | ML@CMU | Carnegie Mellon University"
url: https://daily.dev/posts/machine-learning-blog-ml-cmu-carnegie-mellon-university-9bh8ft513
source_url: https://blog.ml.cmu.edu/2024/04/12/how-to-regularize-your-regression/
type: article
source: "ML CMU"
published: 2024-04-13T03:26:43.678Z
updated: 2024-05-09T08:58:27.770Z
tags: ["machine-learning", "linear-regression"]
reading_time: 15
upvotes: 2
comments: 0
language: en
---

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# Machine Learning Blog | ML@CMU | Carnegie Mellon University

**[ML CMU](https://daily.dev/sources/mlcmu)** · 15 min read · 2 upvotes · 0 comments

## Summary

This post discusses the use of linear regression with regularization and the challenges of setting the regularization parameters. It introduces the concept of data-driven algorithm design and provides sample complexity guarantees for learning the optimal parameters. The post also explores the extension to binary classification and kernel regression. The research opens up possibilities for tuning learnable parameters in continuous optimization problems.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://blog.ml.cmu.edu/2024/04/12/how-to-regularize-your-regression/>

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---

Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#linear-regression](https://daily.dev/tags/linear-regression)

[View this post on daily.dev](https://daily.dev/posts/machine-learning-blog-ml-cmu-carnegie-mellon-university-9bh8ft513)