Henryk Blasinski




Henryk is a PhD candidate in the Electrical Engineering Department where he is a member of the VISTA Lab. His scientific interests focus on applying convex optimization and machine learning techniques to solving problems in multispectral imaging and computer vision. In his free time Henryk is an avid sailor.

More info: http://www.stanford.edu/~hblasins/

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Jan 21st 2014

This course concentrates on recognizing and solving convex optimization problems that arise in applications. The syllabus includes: convex sets, functions, and optimization problems; basics of convex analysis; least-squares, linear and quadratic programs, semidefinite programming, minimax, extremal volume, and other problems; optimality conditions, duality theory, theorems of alternative, and applications; interior-point methods; applications to signal processing, statistics and machine learning, control and mechanical engineering, digital and analog circuit design, and finance.

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