Abstract
Our final chapter provides a concrete introduction to convex programming, interior point methods, and duality, three of the deepest and most pervasive themes of modern optimization theory. It takes considerable mathematical maturity to appreciate the subtlety of these topics, and it is impossible to do them justice in a short essay. Our philosophy here is to build on previous material on convexity and the MM algorithm. Exposing these connections reinforces old concepts while teaching new ones. The survey article [46] is especially recommended to readers wanting a more thorough introduction to the topics treated here.
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© 2004 Springer Science+Business Media New York
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Lange, K. (2004). Convex Programming. In: Optimization. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-4182-7_11
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DOI: https://doi.org/10.1007/978-1-4757-4182-7_11
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-1910-6
Online ISBN: 978-1-4757-4182-7
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