Convex Optimization

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• Stephen P. Boyd, Samsung Professor in the School of Engineering, Stanford University
• Friday 26 January 2018, 12:00-13:00
• Department of Engineering - LT2.

If you have a question about this talk, please contact Dr Timothy O'Leary.

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.

This talk is part of the Information Engineering Distinguished Lecture Series series.

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