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» Parallel matrix algorithms and applications
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90
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PPSC
1993
15 years 1 months ago
Parallel Preconditioning and Approximate Inverses on the Connection Machine
We present a new approach to preconditioning for very large, sparse, non-symmetric, linear systems. We explicitly compute an approximate inverse to our original matrix that can be...
Marcus J. Grote, Horst D. Simon
TPDS
1998
157views more  TPDS 1998»
15 years 5 days ago
A Compiler Optimization Algorithm for Shared-Memory Multiprocessors
This paper presents a new compiler optimization algorithm that parallelizes applications for symmetric, sharedmemory multiprocessors. The algorithm considers data locality, parall...
Kathryn S. McKinley
93
Voted
CORR
2010
Springer
225views Education» more  CORR 2010»
15 years 19 days 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...
107
Voted
ICASSP
2011
IEEE
14 years 4 months ago
Unsupervised vocabulary discovery using non-negative matrix factorization with graph regularization
In this paper, we present a model for unsupervised pattern discovery using non-negative matrix factorization (NMF) with graph regularization. Though the regularization can be appl...
Meng Sun, Hugo Van hamme
102
Voted
ICASSP
2011
IEEE
14 years 4 months ago
Low-rank matrix completion by variational sparse Bayesian learning
There has been a significant interest in the recovery of low-rank matrices from an incomplete of measurements, due to both theoretical and practical developments demonstrating th...
S. Derin Babacan, Martin Luessi, Rafael Molina, Ag...