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Semidefinite optimization and convex algebraic geometry.


Semidefinite optimization and convex algebraic geometry.

Ed. by Grigoriy Blekherman, Pablo A. Parrilo and Rekha R. Thomas.



476 pages


MOS-SIAM series on optimization


The first two chapters in this graduate textbook generalize linear programming to convex optimization problems and introduce semidefinite optimization as the algorithmic engine behind computing sum of squares decompositions of polynomials. The other six contributions examine the relationship between nonnegativity and sums of squares, compare the different notions of duality, find spectrahedral approximations of convex hulls of algebraic sets, extend algebraic certificates of real algebraic geometry to noncommutative polynomials, and derive sums of Hermitian squares.

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Title Annotation:MOS-SIAM Series on Optimization
Publication:Reference & Research Book News
Article Type:Brief article
Date:Apr 1, 2013
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