Preprints

• Performance comparison of greedy algorithms in compressed sensing, Jeffrey D. Blanchard and Jared Tanner.
• An exact tree projection algorithm for wavelets, Coralia Cartis and Andrew Thompson.
• Alternating maximization: Unifying framework for 8 sparse PCA formulations and efficient parallel codes, Peter Richtarik, Martin Takac, and S. Damla Ahipasaoglu.
• Parallel coordinate descent methods for big data optimization, Peter Richtarik and Martin Takac.
• Vanishingly Sparse Matrices and Expander Graphs, with application to compressed sensing, Bubacarr Bah and Jared Tanner.
• GPU accelerated greedy algorithms for compressed sensing, Jeffrey D. Blanchard and Jared Tanner.
• Normalized iterative hard thresholding for matrix completion, Jared Tanner and Ke Wei.
• Recovery guarantees for rank aware pursuits, Jeffrey D. Blanchard and Mike E. Davies.
  Video of original presentation.
• Bounds of restricted isometry constants in extreme asymptotics: formulae for Gaussian matrices, Bubacarr Bah and Jared Tanner.
• Iteration complexity of randomized block-coordinate descent methods for minimizing a composite function, Peter Richtarik and Martin Takac.
• Compressible priors for high-dimensional statistics, Remi Gribonval, Volkan Cevher, and Mike E. Davies.
• Reconciling compressive sampling systems for spectrally-sparse continuous-time signals, Michael Lexa, Mike E. Davies, and John Thompson.
• Compressive power spectral density estimation, Michael Lexa, Mike E. Davies, John Thompson, and Janosch Nikolic.
• Rank awareness in joint sparse recovery, Mike E. Davies and Yonina C. Eldar.
• Non-convexly constrained linear inverse problems , Thomas Blumensath.
• Sampling and reconstructing signals from a union of linear subspaces, Thomas Blumensath.

Published in 2011

• Compressive single-pixel imaging: a technical report, Andrew Thompson.
• Compressed Sensing: How sharp is the Restricted Isometry Property?, Jeffrey D. Blanchard, Coralia Cartis, and Jared Tanner; SIAM Review, Vol. 53(1), (2011), 105-125.
• Phase transitions for greedy sparse approximation algorithms, Jeffrey D. Blanchard, Coralia Cartis, Jared Tanner, and Andrew Thompson Applied and Computational Harmonic Analysis, Vol. 30(2) (2011) 188-203.

Published in 2010

• Improved bounds on restricted isometry constants for Gaussian matrices, Bubacarr Bah and Jared Tanner; SIAM Journal on Matrix Analysis , Vol. 31(5) (2010) 2882-2898.
• On support sizes of restricted isometry constants, Jeffrey D. Blanchard and Andrew Thompson; Applied and Computational Harmonic Analysis, Vol. 29(3) (2010) 382-390.
• Precise Undersampling Theorems, David L. Donoho and Jared Tanner; Proceedings of the IEEE , Vol. 98(6), (2010), 913-924.
• Exponential bounds implying construction of compressed sensing matrices, error-correcting codes and neighborly polytopes by random sampling, David L. Donoho and Jared Tanner; IEEE Transactions on Information Theory, Vol. 56(4), (2010), 2002-2016.
• Normalised Iterative Hard Thresholding; guaranteed stability and performance, Thomas Blumensath and Mike E. Davies; IEEE Journal of Selected Topics in Signal Processing, Vol. 4(2), (2010), 298-309.
• Generalized power method for sparse principal component analysis, Michel Journee, Yurii Nesterov, Peter Richtarik, and Rodolphe Sepulchre; Journal of Machine Learning Research, Vol. 11(2), (2010), 517-553.
• Counting the faces of randomly-projected hypercubes and orthants, with applications, David L. Donoho and Jared Tanner; Discrete and Computational Geometry, Vol. 43(3), (2010), 522-541.

Published in 2009

• Observed universality of phase transitions in high-dimensional geometry, with implications for modern data analysis and signal processing, David L. Donoho and Jared Tanner; Philosophical Transactions of the Royal Society A, Vol. 367(1906), (2009) 4273--4293.
• Stagewise Weak Gradient Pursuits, Thomas Blumensath and Mike E. Davies; IEEE Transactions on Signal Processing, Vol. 57(11), (2009) 4333--4346.
• Restricted Isometry Constants where Lp sparse recovery can fail for p in (0,1],, M. E. Davies and R. Gribonval; IEEE Trans. Information Theory, Vol. 55(5), (2009), 2203--2214
• Iterative Hard Thresholding for Compressed Sensing, Thomas Blumensath and Mike E. Davies; Applied and Computational Harmonic Analysis,, Vol. 27(3), (2009) 265--274.
• Decay properties for restricted isometry constants, Jeffrey D. Blanchard, Coralia Cartis, and Jared Tanner; IEEE Signal Processing Letters, Vol. 16(7), (2009) 572--575.
• Sampling Theorems for Signals from the Union of Finite-Dimensional Linear Subspaces, Thomas Blumensath and Mike E. Davies; IEEE Transactions on Information Theory, Vol. 55(4), (2009) 1872--1882.
• Compressed sensing signal models - to infinity and beyond?, T. Blumensath and M. E. Davies; Proc. SAMPTA 2009(2009).
• On Lp minimisation, instance optimality and restricted isometry constants for sparse approximation, M. E. Davies and R. Gribonval; Proc. SAMPTA 2009 (2009).
• Compressed sensing based compression of SAR raw data, Gabriel Rilling, Mike Davies and Bernard Mulgrew; Proc. of SPARS'09 (Signal Processing with Adaptive Sparse Structured Representations), Saint-Malo (F), April 2009.
• Phase transitions for restricted isometry properties, Jeffrey D. Blanchard, Coralia Cartis, and Jared Tanner; Proc. of SPARS'09 (Signal Processing with Adaptive Sparse Structured Representations), Saint-Malo (F), April 2009.
• Restricted Isometry Constants where lp sparse recovery can fail for p in (0,1].,M. E. Davies and R. Gribonval; Proc. of SPARS'09 (Signal Processing with Adaptive Sparse Structured Representations), Saint-Malo (F), April 2009.
• How to use the Iterative Hard Thresholding algorithm, Thomas Blumensath and Mike E. Davies; Proc. of SPARS'09 (Signal Processing with Adaptive Sparse Structured Representations), Saint-Malo (F), April 2009.
• Compressed sensing based compression of SAR raw data, G. Rilling, M. E. Davies, B. Mulgrew; Proc. of SPARS09(2009)
• A Simple, Efficient and Near Optimal Algorithm for Compressed Sensing, Thomas Blumensath and Mike E. Davies; in Proc. of ICASSP, Tainpei, Taiwan, (2009).
• Counting faces of randomly-projected polytopes when the projection radically lowers dimension, David L. Donoho and Jared Tanner; Journal of the AMS, Vol. 22(1), (2009) 1--53.

Published in 2008

• Identification of Matrices having a Sparse Representation, Gotz E. Pfander, Holger Rauhut, and Jared Tanner;IEEE Transactions on Signal Processing, Vol. 56(11), (2008) 5376--5388.
• Iterative Thresholding for Sparse Approximations, Thomas Blumensath and Mike E. Davies; The Journal of Fourier Analysis and Applications, Vol. 14(5), (2008) 629--654.
• Gradient Pursuits, Thomas Blumensath and Mike E. Davies; IEEE Transactions on Signal Processing, Vol. 56(6), (2008) 2370--2382.
• Gradient Pursuit for Non-Linear Sparse Signal Modelling, Thomas Blumensath and Mike E. Davies; Proc. of the European Signal Processing Conference (EUSIPCO), Lausanne, Switzerland, (2008).

Published in 2007

• Faster & Greedier: algorithms for sparse reconstruction of large datasets, Mike E. Davies and Thomas Blumensath;invited paper to the third IEEE International Symposium on Communications, Control, and Signal Processing, St Julians, Malta, (2007).
• Fast encoding of synthetic aperture radar raw data using compressed sensing, Sujit Bhattacharya, Thomas Blumensath, Bernard Mulgrew and Mike E. Davies; Proc. of IEEE Workshop on Statistical Signal Processing, Madison, USA, (2007).
• Compressed Sensing and Source Separation, Thomas Blumensath and Mike E. Davies; Proc. of International Conference on Independent Component Analysis and Signal Separation, London, UK, (2007).
• In Greedy Pursuit of New Directions: (Nearly) Orthogonal Matching Pursuit by Directional Optimisation, Thomas Blumensath and Mike E. Davies; in Proc. of the European Signal Processing Conference (EUSIPCO), Poznan, Poland,(2007).
• Iterative Hard Thresholding and L0 Regularisation, Thomas Blumensath, Mehrdad Yaghoobi and Mike E. Davies; Proc. of the IEEE International Conference on Acoustics, Speech and Signal Processing, Honolulu, USA, (2007).

Published in 2006

• Thresholds for the Recovery of Sparse Solutions via L1 Minimization, David L. Donoho and Jared Tanner; Proceedings of the Conference on Information Sciences and Systems, March 2006.

Published in 2005

• Neighborliness of Randomly-Projected Simplices in High Dimensions, David L. Donoho and Jared Tanner; Proceedings of the National Academy of Sciences, Vol. 102(27), (2005) 9452--9457.
• Sparse Nonnegative Solutions of Underdetermined Linear Equations by Linear Programming, David L. Donoho and Jared Tanner; Proceedings of the National Academy of Sciences, Vol. 102(27), (2005) 9446--9451.