Stable Manifold Embeddings With Structured Random Matrices

Abstract
The fields of compressed sensing (CS) and matrix completion have shown that high-dimensional signals with sparse or low-rank structure can be effectively projected into a low-dimensional space (for efficient acquisition or processing) when the projection operator achieves a stable embedding of the data by satisfying the Restricted Isometry Property (RIP). It has also been shown that such stable embeddings can be achieved for general Riemannian...
Paper Details
Title
Stable Manifold Embeddings With Structured Random Matrices
DOI
Published Date
Aug 1, 2013
Journal
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