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PPSC
1997
15 years 1 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 1 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 6 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 1 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
97
Voted
COMPUTING
2006
119views more  COMPUTING 2006»
15 years 16 days 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