A note on element-wise matrix sparsification via a matrix-valued Bernstein inequality

[1]  Joel A. Tropp,et al.  User-Friendly Tail Bounds for Sums of Random Matrices , 2010, Found. Comput. Math..

[2]  David Gross,et al.  Recovering Low-Rank Matrices From Few Coefficients in Any Basis , 2009, IEEE Transactions on Information Theory.

[3]  Benjamin Recht,et al.  A Simpler Approach to Matrix Completion , 2009, J. Mach. Learn. Res..

[4]  Trac D. Tran,et al.  Tensor sparsification via a bound on the spectral norm of random tensors , 2010, ArXiv.

[5]  Emmanuel J. Candès,et al.  The Power of Convex Relaxation: Near-Optimal Matrix Completion , 2009, IEEE Transactions on Information Theory.

[6]  Nam H. Nguyen,et al.  Matrix sparsification via the Khintchine inequality , 2010 .

[7]  Alex Gittens,et al.  Error Bounds for Random Matrix Approximation Schemes , 2009, 0911.4108.

[8]  Emmanuel J. Candès,et al.  Exact Matrix Completion via Convex Optimization , 2008, Found. Comput. Math..

[9]  Alexandre d'Aspremont,et al.  Subsampling algorithms for semidefinite programming , 2008, 0803.1990.

[10]  Sanjeev Arora,et al.  A Fast Random Sampling Algorithm for Sparsifying Matrices , 2006, APPROX-RANDOM.

[11]  Petros Drineas,et al.  Fast Monte Carlo Algorithms for Matrices I: Approximating Matrix Multiplication , 2006, SIAM J. Comput..

[12]  Sanjeev Arora,et al.  Fast algorithms for approximate semidefinite programming using the multiplicative weights update method , 2005, 46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05).

[13]  R. M. Dijkstra.  Information Processing Letters , 2003 .

[14]  Dimitris Achlioptas,et al.  Fast computation of low rank matrix approximations , 2001, STOC '01.