495 search results - page 8 / 99 » Sparse representation algorithms based on mean-field approxi... |
165
Voted
ISCAS
2008
IEEE
15 years 10 months ago
2008
IEEE
— Non-negative matrix factorization (NMF), i.e. V ≈ WH where both V, W and H are non-negative has become a widely used blind source separation technique due to its part based r...
132
Voted
CORR
2010
Springer
15 years 4 months ago
2010
Springer
Recent work has demonstrated that using a carefully designed sensing matrix rather than a random one, can improve the performance of compressed sensing. In particular, a welldesign...
145
Voted
ICASSP
2011
IEEE
14 years 7 months ago
2011
IEEE
We introduce the Multiplicative Update Selector and Estimator (MUSE) algorithm for sparse approximation in underdetermined linear regression problems. Given f = Φα∗ + µ, the ...
133
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ICASSP
2011
IEEE
14 years 7 months ago
2011
IEEE
Sparse representations over redundant dictionaries offer an efficient paradigm for signal representation. Recently block-sparsity has been put forward as a prior condition for so...
123
Voted
JMLR
2010
14 years 10 months ago
2010
We present a new sparse Gaussian Process (GP) model for regression. The key novel idea is to sparsify the spectral representation of the GP. This leads to a simple, practical algo...