New and Improved Johnson–Lindenstrauss Embeddings via the Restricted Isometry Property

Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions

(2011) N. Halko et al.   SIAM REVIEW

Compressed sensing with coherent and redundant dictionaries

(2010) Emmanuel J. Candès et al.   APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS

Beyond Nyquist: Efficient Sampling of Sparse Bandlimited Signals

(2010) Joel A. Tropp et al.   IEEE TRANSACTIONS ON INFORMATION THEORY

The Gelfand widths of ℓp-balls for 0<p≤1

(2010) Simon Foucart et al.   JOURNAL OF COMPLEXITY

A variant of the Johnson–Lindenstrauss lemma for circulant matrices

(2010) Jan Vybíral   JOURNAL OF FUNCTIONAL ANALYSIS

A note on guaranteed sparse recovery via ℓ1-minimization

(2009) Simon Foucart   APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS

Compressed Sensing With Cross Validation

(2009) Rachel Ward   IEEE TRANSACTIONS ON INFORMATION THEORY

Compressive Sensing by Random Convolution

(2009) Justin Romberg   SIAM Journal on Imaging Sciences

A Simple Proof of the Restricted Isometry Property for Random Matrices

(2008) Richard Baraniuk et al.   CONSTRUCTIVE APPROXIMATION

On sparse reconstruction from Fourier and Gaussian measurements

(2007) Mark Rudelson et al.   COMMUNICATIONS ON PURE AND APPLIED MATHEMATICS