Convex Optimization Stephen Boyd 26 January 2018
Duration: 1 hour 2 mins
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| Description: | Convex optimization has emerged as useful tool for applications that include data analysis and model fitting, resource allocation, engineering design, network design and optimization, finance, and control and signal processing. After an overview of the mathematics, algorithms, and software frameworks for convex optimization, we turn to common themes that arise across applications, such as sparsity and relaxation. We describe recent work on real-time embedded convex optimization, in which small problems are solved repeatedly in millisecond or microsecond time frames, and large-scale distributed convex optimization, in which many solvers are coordinated to solve enormous problems. |
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| Created: | 2019-03-25 09:54 |
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| Collection: | Information Engineering Distinguished Lecture Series |
| Publisher: | University of Cambridge |
| Copyright: | Stephen Boyd |
| Language: | eng (English) |
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