The Convex Geometry of Linear Inverse Problems

In applications throughout science and engineering one is often faced with the challenge of solving an ill-posed inverse problem, where the number of available measurements is smaller than the dimension of the model to be estimated. However in many practical situations of interest, models are constr...

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Bibliographic Details
Published in:	Foundations of computational mathematics Vol. 12; no. 6; pp. 805 - 849
Main Authors:	Chandrasekaran, Venkat, Recht, Benjamin, Parrilo, Pablo A., Willsky, Alan S.
Format:	Journal Article
Language:	English
Published:	New York Springer-Verlag 01.12.2012 Springer Nature B.V
Subjects:	Algebra Applications of Mathematics Atomic structure Computational mathematics Computer Science Economics Geometry Inverse problems Linear and Multilinear Algebras Math Applications in Computer Science Mathematical analysis Mathematical models Mathematics Mathematics and Statistics Matrices Matrix methods Matrix Theory Norms Numerical Analysis Optimization Programming 60D05 41A45 Semidefinite programming 52A41 Convex optimization 90C25 90C22 Atomic norms Real algebraic geometry Gaussian width Symmetry
ISSN:	1615-3375, 1615-3383
Online Access:	Get full text
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