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Corrupted Sensing: Novel Guarantees for Separating Structured Signals
Corrupted sensing compressed sensing deconvolution error correction structured signal sparsity block sparsity low rank atomic norms ℓ 1 minimization
2013/6/14
We study the problem of corrupted sensing, a generalization of compressed sensing in which one aims to recover a signal from a collection of corrupted or unreliable measurements. While an arbitrary si...
Coherence-Based Performance Guarantees of Orthogonal Matching Pursuit
Compressive Sensing(CS) Orthogonal Matching Pursuit(OMP) worst-case coherence average coherence support recovery signal reconstruction
2012/11/23
In this paper, we present coherence-based performance guarantees of Orthogonal Matching Pursuit (OMP) for both support recovery and signal reconstruction of sparse signals when the measurements are co...
Performance guarantees for individualized treatment rules
Decision making l1-penalized least squares value
2011/6/17
Because many illnesses show heterogeneous response to treatment,
there is increasing interest in individualizing treatment to patients
[Arch. Gen. Psychiatry 66 (2009) 128–133]. An individualized
t...
Concentration-Based Guarantees for Low-Rank Matrix Reconstruction
Low-Rank Matrix Reconstruction
2011/3/25
We consider the problem of approximately reconstructing a partially-observed, approximately low-rank matrix. This problem has received much attention lately, mostly using the trace-norm as a surrogate...
Coherence-Based Performance Guarantees for Estimating a Sparse Vector Under Random Noise
Coherence-Based Performance Guarantees Sparse Vector Random Noise
2010/3/19
We consider the problem of estimating a deterministic
sparse vector x0 from underdetermined measurements
Ax0 + w, where w represents white Gaussian noise and A is
a given deterministic dictionary. ...