Optimization@MIT

6.256 -- Algebraic Techniques and Semidefinite Optimization
Course Description: Theory and computational techniques for optimization problems involving polynomial equations and inequalities with particular, emphasis on the connections with semidefinite optimization. Develops algebraic and numerical approaches of general applicability, with a view towards methods that simultaneously incorporate both elements, stressing convexity-based ideas, complexity results, and efficient implementations. Examples from several engineering areas, in particular systems and control applications. Topics include semidefinite programming, resultants/discriminants, hyperbolic polynomials, Groebner bases, quantifier elimination, and sum of squares.

This class is at the Graduate level
Instructor: P. Parrilo
Prerequisites: 6.251J or 6.255J

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