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PPSC
1997
15 years 3 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
ICML
2006
IEEE
16 years 3 months ago
Convex optimization techniques for fitting sparse Gaussian graphical models
We consider the problem of fitting a large-scale covariance matrix to multivariate Gaussian data in such a way that the inverse is sparse, thus providing model selection. Beginnin...
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...
ECML
2007
Springer
15 years 8 months ago
Stability Based Sparse LSI/PCA: Incorporating Feature Selection in LSI and PCA
The stability of sample based algorithms is a concept commonly used for parameter tuning and validity assessment. In this paper we focus on two well studied algorithms, LSI and PCA...
Dimitrios Mavroeidis, Michalis Vazirgiannis
NIPS
2008
15 years 3 months ago
Differentiable Sparse Coding
Prior work has shown that features which appear to be biologically plausible as well as empirically useful can be found by sparse coding with a prior such as a laplacian (L1) that...
J. Andrew Bagnell, David M. Bradley
COMPUTING
2006
119views more  COMPUTING 2006»
15 years 2 months ago
Sparse Grids, Adaptivity, and Symmetry
Sparse grid methods represent a powerful and efficient technique for the representation and approximation of functions and particularly the solutions of partial differential equat...
Harry Yserentant