Lecture 4 | Convex Optimization Principles | Convex Optimization by Dr. Ahmad Bazzi

☕️ Buy me a coffee: https://paypal.me/donationlink240 🙏🏻 Support me on Patreon: https://www.patreon.com/c/ahmadbazzi In Lecture 4 of this course on convex optimization, we will be covering the fundamental principles of convex optimization, which include the following: 00:00 Standard form 04:19 Feasible point 05:07 Globally Optimum point 05:50 Locally Optimum point 15:04 Explicit & Implicit constraints 30:10 Optimality criterion for differentiable cost functions 34:48 Supporting Hyperplane --------------------------------------------------------------------------------------------------------- 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 --------------------------------------------------------------------------------------------------------- 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. --------------------------------------------------------------------------------------------------------- Instructor: Dr. Ahmad Bazzi IG: https://www.instagram.com/drahmadbazzi/ FB: https://www.facebook.com/profile.php?id=100002083151128 RG: https://www.researchgate.net/profile/Ahmad_Bazzi MSE: https://math.stackexchange.com/users/310385/ahmad-bazzi?tab=profile YT: https://www.youtube.com/c/AhmadBazzi --------------------------------------------------------------------------------------------------------- Credits : Microsoft OneNote: https://products.office.com/en-gb/onenote MATLAB: https://www.mathworks.com/products/matlab.html #ConvexOptimization #Convex #Optimization