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In Lecture 7 of this course on convex optimization, we will cover the essentials of Quadratically Constrained Quadratic Programs, i.e. QCQPs.The outline of the lecture is as follows:
00:00 Intro
00:33 What is a Quadratically Constrained Quadratic Program (QCQP) ?
05:16 QCQP Feasible Set
06:01 MATLAB Illustration of QCQP Feasible Set
13:39 QCQP Application 1: Minimizing a linear function over a centered ellipsoid
30:42 QCQP Application 2: Minimizing a linear function over an uncentered ellipsoid
37:16 QCQP Application 3: Minimizing a quadratic function over a centered ellipsoid
42:36 Outro
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Lecture 1 | Introduction to Convex Optimization:
https://youtu.be/SHJuGASZwlE
Lecture 2 | Convex Sets:
https://youtu.be/QV5qtTq1Tro
Lecture 3 | Convex Functions:
https://youtu.be/XzW-B1CJ_ao
Lecture 4 | Convex Optimization Principles :
https://youtu.be/aMC3WPGMLes
Lecture 5 | Linear Programming & SIMPLEX algorithm w MATLAB:
https://youtu.be/dAyeNmz6p-c
Lecture 6 | Quadratic Programs:
https://youtu.be/kM52hSvBY4k
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References:
[1] Boyd, Stephen, and Lieven Vandenberghe. Convex optimization. Cambridge university press, 2004.
[2] Nesterov, Yurii. Introductory lectures on convex optimization: A basic course. Vol. 87. Springer Science & Business Media, 2013.
Reference no. 3:
[3] Ben-Tal, Ahron, and Arkadi Nemirovski. Lectures on modern convex optimization: analysis, algorithms, and engineering applications. Vol. 2. Siam, 2001.
[4] Bazzi, Ahmad, Dirk TM Slock, and Lisa Meilhac. "Online angle of arrival estimation in the presence of mutual coupling." 2016 IEEE Statistical Signal Processing Workshop (SSP). IEEE, 2016.
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Instructor: Dr. Ahmad Bazzi
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Credits :
Microsoft OneNote: https://products.office.com/en-gb/onenote
MATLAB: https://www.mathworks.com/products/matlab.html
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