6.256 Algebraic Techniques and Semidefinite Optimization

Class Info

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 has 6.251, and 6.255 as prerequisites.

6.256 will not be offered this semester. It will be available in the Spring semester, and will be instructed by P. Parrilo.

Lecture occurs 1:00 PM to 2:30 PM on Wednesdays and Fridays in 34-301.

This class counts for a total of 12 credits.

In the Spring 2016 Subject Evaluations, 6.256 was rated 5.8 out of 7.0. You can find more information at the Optimization at MIT: 6.256 site or on the 6.256 Stellar site.

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