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Lecture 1 | Convex Optimization I (Stanford)

Stanford · lecture · Watch on YouTube

University lectures & coursesPure mathematicsMath & theory (other)

What it is

The introductory lecture of Stephen Boyd's Stanford Convex Optimization I course (EE 364A). It outlines convex sets, functions and problems, and the course's coverage of least-squares, linear and semidefinite programming, duality and interior-point methods.

Why Hacker News recommends it

HN recommends Boyd's lectures as a fantastic, often funny follow-up to linear algebra and as a step in machine learning study paths.

  • 2 people recommended it
  • 2 different months
  • 1 strong recommendations
  • first 2011, last 2022

What HN commenters said

  1. “These lectures are fantastic after you've mastered the basics of linear algebra”

    Fantastic, often funny convex optimization lectures by an experienced lecturer.

    natly, 2022-05 · Strong recommendation · in “The big six matrix factorizations”

  2. “Steven Boyds astounding convex optimization lectures”

    Boyd's lectures give an intuitive way to think about matrix multiplication.

    hwers, 2022-01 · Recommendation · in “Matrix Multiplication”

Excerpts from Hacker News comments, linked to the originals. Summaries and labels were written by a language model from those comments.

Topics: convex optimization, stanford, linear algebra, duality, stephen boyd

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