Lecture 14: LU Factorization (Cont.)

author: Stephen P. Boyd, Department of Electrical Engineering, Stanford University
published: Aug. 17, 2010,   recorded: January 2008,   views: 3536
released under terms of: Creative Commons Attribution Non-Commercial (CC-BY-NC)

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That’s all. One factor, two back solves. Okay. Now we need to get to something very important. A lot of you probably haven’t seen it. It’s probably – it’s one of the most important topics, which I believe is basically not covered because it falls between the cracks. It’s covered somewhere deep into some class on the horrible fine details of numerical computing or something like that, I guess. I don’t think it’s well enough covered, at least from the people I hang out with – not enough of them know about it. And it has to do with them exploiting sparsity in numerical algebra. So if a matrix A is sparse, you can factor it as P1LUP2. ...

See the whole transcript at Convex Optimization I - Lecture 14

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Reviews and comments:

Comment1 Bart Alder, August 29, 2010 at 6:28 p.m.:

The video keeps cutting out. It just stops after a few minutes. Not sure why. I tried watching it twice and got five or so minutes in before it cut out again and I gave up at that point.

Looked like a good lecture too. : (

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