Lecture 5: Optimal And Locally Optimal Points
published: Aug. 17, 2010, recorded: January 2008, views: 3688
released under terms of: Creative Commons Attribution Non-Commercial (CC-BY-NC)
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Am I gonna discuss generalized inequalities? No. That was the question. That was my answer, too. No. No, it’s clear enough in the book. And when we get to something where it’s relevant, like experiment design – it’ll also be relevant in detection and estimation, then I’ll go back over it. Also in multi-criterion optimization which we’re gonna do later. So I’ll go back over it. Okay. So today we’re gonna go through optimization problems. The first part is a bit boring. It’s just setting down basic terminology like what does it mean to be feasible, what are the constraint sets, actually what is a convex optimization problem, but then it’ll transition to actually useful, so you actually find out about what a linear program is, what a quadratic program is, second order cone program, and these types of things. ...
See the whole transcript at Convex Optimization I - Lecture 05
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !