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Sparse Bayesian Methods for Low-Rank Matrix Estimation
Low-Rank Matrix Estimation Sparse Bayesian Methods
2011/3/24
Recovery of low-rank matrices has recently seen significant activity in many areas of science and engineering, motivated by recent theoretical results for exact reconstruction guarantees and interesti...
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...
On Low Rank Matrix Approximations with Applications to Synthesis Problem in Compressed Sensing
Low Rank Matrix Approximations Applications Synthesis Problem Compressed Sensing
2010/3/9
We consider the synthesis problem of Compressed Sensing –given s and an M×n
matrix A, extract from it an m × n submatrix Am, certified to be s-good, with m
as small as possible. Starting from the ve...