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 be offered this semester (Spring 2018). It is instructed by .

This class counts for a total of 12 credits. This is a graduate-level class.

You can find more information at the Optimization at MIT: 6.256 site or on the 6.256 Stellar site.

MIT 6.256 Algebraic Techniques and Semidefinite Optimization Related Textbooks
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