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CORR
2012
Springer
13 years 5 months ago
2012
Springer
We consider the problem of recovering a target matrix that is a superposition of low-rank and sparse components, from a small set of linear measurements. This problem arises in co...
118
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CVPR
2011
IEEE
14 years 6 months ago
2011
IEEE
Compressive Sensing has become one of the standard methods of face recognition within the literature. We show, however, that the sparsity assumption which underpins much of this w...
76
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CORR
2010
Springer
14 years 10 months ago
2010
Springer
Recent work has demonstrated that using a carefully designed sensing matrix rather than a random one, can improve the performance of compressed sensing. In particular, a welldesign...
ICIP
2009
IEEE
15 years 10 months ago
2009
IEEE
In this paper, following the Compressed Sensing (CS) paradigm, we study the problem of recovering sparse or compressible signals from uniformly quantized measurements. We present ...
CORR
2010
Springer
14 years 10 months ago
2010
Springer
A new framework of compressive sensing (CS), namely statistical compressive sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical dist...