Convex Optimization & Euclidean Distance Geometry 论文

2004引用 497
Graph Labeling and Dimension ProblemsDigital Image Processing TechniquesMathematics and Applications

详细信息

发表日期
2004-01-01
发表年份
2004

关键词

Graph Labeling and Dimension ProblemsDigital Image Processing TechniquesMathematics and Applications

摘要

Optimization is the science of making a best choice in the face of conflicting requirements. Any convex optimization problem has geometric interpretation. If a given optimization problem can be transformed to a convex equivalent, then this interpretive benefit is acquired. That is a powerful attraction: the ability to visualize geometry of an optimization problem. Conversely, recent advances in geometry hold convex optimization within their proofs' core. This book is about convex optimization, convex geometry (with particular attention to distance geometry), geometrical problems, and problems that can be transformed into geometrical problems. Euclidean distance geometry is, fundamentally, a determination of point conformation from interpoint distance information; e.g., given only distance information, determine whether there corresponds a realizable configuration of points; a list of points in some dimension that attains the given interpoint distances. large black & white paperback

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