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ISCAS
2008
IEEE
217views Hardware» more  ISCAS 2008»
14 years 1 months ago
Approximate L0 constrained non-negative matrix and tensor factorization
— 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...
Morten Mørup, Kristoffer Hougaard Madsen, L...
CORR
2010
Springer
225views Education» more  CORR 2010»
13 years 7 months ago
Sensing Matrix Optimization for Block-Sparse Decoding
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...
Kevin Rosenblum, Lihi Zelnik-Manor, Yonina C. Elda...
ICASSP
2011
IEEE
12 years 10 months ago
Compressive sensing meets game theory
We introduce the Multiplicative Update Selector and Estimator (MUSE) algorithm for sparse approximation in underdetermined linear regression problems. Given f = Φα∗ + µ, the ...
Sina Jafarpour, Robert E. Schapire, Volkan Cevher
ICASSP
2011
IEEE
12 years 11 months ago
A clustering based framework for dictionary block structure identification
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...
Ender M. Eksioglu
JMLR
2010
112views more  JMLR 2010»
13 years 1 months ago
Sparse Spectrum Gaussian Process Regression
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...
Miguel Lázaro-Gredilla, Joaquin Quiñ...