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Quadratic Optimization Problems

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Geometric Methods and Applications

Part of the book series: Texts in Applied Mathematics ((TAM,volume 38))

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Abstract

In this chapter, we consider two classes of quadratic optimization problems that appear frequently in engineering and in computer science (especially in computer vision): 1. Minimizing

$$f(x)=\frac{1}{2}x^\top Az+x^\top b$$

over all \(x \varepsilon \mathbb{R}^n\), or subject to linear or affine constraints. 2. Minimizing

$$f(x)=\frac{1}{2}x^\top Az+x^\top b$$

over the unit sphere.

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Author information

Authors and Affiliations

  1. Department of Computer and Information Science, University of Pennsylvania, 3330 Walnut Street, Philadelphia, PA, 19104, USA

    Jean Gallier

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  1. Jean Gallier
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Correspondence to Jean Gallier .

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© 2011 Springer Science+Businees Media, LLC

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Gallier, J. (2011). Quadratic Optimization Problems. In: Geometric Methods and Applications. Texts in Applied Mathematics, vol 38. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-9961-0_15

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