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The Restricted Isometry Property (RIP) is a fundamental property of a matrix which enables sparse recovery.
Increasing properties of Pólya frequency functions
Bradley Efron · 1965
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Integral limit theorems taking large deviations into account when Cramér’s condition does not hold. I
A.V. Nagaev · 1969
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Integral limit theorems taking large deviations into account when Cramér’s condition does not hold. II
A.V. Nagaev · 1969
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Negative association of random variables with applications
Kumar Joag-Dev and Frank Proschan · 1983
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Estimation of moments of sums of independent real random variables
Rafał Latała · 1997
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Randomized distributed edge coloring via an extension of the Chernoff-Hoeffding bounds
Alessandro Panconesi and Aravind Srinivasan · 1997
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Are bitvectors optimal?
Harry Buhrman, Peter Bro Miltersen, Jaikumar Radhakrishnan, and Srinivasan Venkatesh · 2002
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Decoding by linear programming
Emmanuel Candès and Terence Tao · 2005
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Metric structures in L 1 L_{1} : dimension, snowflakes, and average distortion
James R. Lee, Manor Mendel, and Assaf Naor · 2005
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Data Streams: Algorithms and Applications
S. Muthukrishnan · 2005
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Stable signal recovery from incomplete and inaccurate measurements
Emmanuel Candès, Justin Romberg, and Terence Tao · 2006
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Compressed sensing
David L. Donoho · 2006
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One sketch for all: fast algorithms for compressed sensing
Anna C. Gilbert, Martin J. Strauss, Joel A. Tropp, and Roman Vershynin · 2007
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A simple proof of the restricted isometry property for random matrices
Richard Baraniuk, Mark Davenport, Ronald DeVore, and Michael Wakin · 2008
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Combining geometry and combinatorics: A unified approach to sparse signal recovery
Radu Berinde, Anna C. Gilbert, Piotr Indyk, Howard Karloff, and Martin J. Strauss · 2008
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Lower bounds for sparse recovery
Khanh Do Ba, Piotr Indyk, Eric Price, and David P. Woodruff · 2010
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Sparse recovery using sparse matrices
Anna C. Gilbert and Piotr Indyk · 2010
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poolMC: Smart pooling of mRNA samples in microarray experiments
Raghunandan M. Kainkaryam, Angela Bruex, Anna C. Gilbert, John Schiefelbein, and Peter J. Woolf · 2010
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Lower bounds on the column sparsity of sparse recovery matrices
Mergen Nachin · 2010
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Compressive sensing and structured random matrices
Holger Rauhut · 2010
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On model-based RIP-1 matrices
Piotr Indyk and Ilya Razenshteyn · 2013
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The restricted isometry property and its implications for compressed sensing
Emmanuel J. Candès · 2008
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Sparse Graph Codes for Compression, Sensing, and Secrecy
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Sparsity lower bounds for dimensionality reducing maps
Jelani Nelson and Huy L. Nguy e ^ ~ \tilde{\hat{\mbox{e}}} n · 2013
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Johnson-Lindenstrauss Compression with Neuroscience-Based Constraints
Zeyuan Allen-Zhu, Rati Gelashvili, Silvio Micali, and Nir Shavit · 2014
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