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

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Загружено: 2019-05-16

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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: • MIT 18.065 Matrix Methods in Data Analysis...

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.

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

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