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PPSC
1997
13 years 8 months ago
Improving Memory-System Performance of Sparse Matrix-Vector Multiplication
Sparse matrix-vector multiplication is an important kernel that often runs inefficiently on superscalar RISC processors. This paper describes techniques that increase instruction-...
Sivan Toledo
PARA
2004
Springer
14 years 25 days ago
Optimization of a Statically Partitioned Hypermatrix Sparse Cholesky Factorization
The sparse Cholesky factorization of some large matrices can require a two dimensional partitioning of the matrix. The sparse hypermatrix storage scheme produces a recursive 2D par...
José R. Herrero, Juan J. Navarro
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
2008
IEEE
14 years 1 months ago
Multiple kernel learning for speaker verification
Many speaker verification (SV) systems combine multiple classifiers using score-fusion to improve system performance. For SVM classifiers, an alternative strategy is to combine...
Chris Longworth, Mark J. F. Gales
JMLR
2006
124views more  JMLR 2006»
13 years 7 months ago
A Direct Method for Building Sparse Kernel Learning Algorithms
Many kernel learning algorithms, including support vector machines, result in a kernel machine, such as a kernel classifier, whose key component is a weight vector in a feature sp...
Mingrui Wu, Bernhard Schölkopf, Gökhan H...