Lecture 11: Minimizing ‖x‖ Subject to Ax = b

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MIT 18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning, Spring 2018 Instructor: Gilbert Strang View the complete course: https://ocw.mit.edu/18-065S18 YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP63oMNUHXqIUcrkS2PivhN3k In this lecture, Professor Strang revisits the ways to solve least squares problems. In particular, he focuses on the Gram-Schmidt process that finds orthogonal vectors. License: Creative Commons BY-NC-SA More information at https://ocw.mit.edu/terms More courses at https://ocw.mit.edu

Published 2019-05-16 · Watch on YouTube ↗
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