Ee 381v: Large Scale Optimization 12.1 Last Time 12.2 Quadratically Constrained Quadratic Program
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چکیده
In the previous lecture, in the first place, we talked about duality for general non-convex optimization. And we know that dual functions are always convex. The dual of the dual problem is also convex. In applications, the dual of the dual can be used as the convex relaxation of the primal (and we will see this explicitly in the next lecture). Then, we covered the concepts of weak duality and strong duality. We proved that weak duality always holds and strong duality always holds for linear programming. This time we will continue the topics about duality, strong duality and related applications.
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