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ICCS
2001
Springer
13 years 9 months ago
Optimizing Sparse Matrix Computations for Register Reuse in SPARSITY
Abstract. Sparse matrix-vector multiplication is an important computational kernel that tends to perform poorly on modern processors, largely because of its high ratio of memory op...
Eun-Jin Im, Katherine A. Yelick
ICCV
2003
IEEE
14 years 6 months ago
Feature Selection for Unsupervised and Supervised Inference: the Emergence of Sparsity in a Weighted-based Approach
The problem of selecting a subset of relevant features in a potentially overwhelming quantity of data is classic and found in many branches of science. Examples in computer vision...
Lior Wolf, Amnon Shashua
PPAM
2005
Springer
13 years 10 months ago
A New Diagonal Blocking Format and Model of Cache Behavior for Sparse Matrices
Algorithms for the sparse matrix-vector multiplication (shortly SpM×V ) are important building blocks in solvers of sparse systems of linear equations. Due to matrix sparsity, the...
Pavel Tvrdík, Ivan Simecek
SIAMNUM
2011
139views more  SIAMNUM 2011»
12 years 11 months ago
Adaptive Wavelet Schemes for Parabolic Problems: Sparse Matrices and Numerical Results
A simultaneous space-time variational formulation of a parabolic evolution problem is solved with an adaptive wavelet method. This method is shown to converge with the best possibl...
Nabi Chegini, Rob Stevenson
FOCS
2008
IEEE
13 years 11 months ago
Near-Optimal Sparse Recovery in the L1 Norm
Abstract— We consider the approximate sparse recovery problem, where the goal is to (approximately) recover a highdimensional vector x ∈ Rn from its lower-dimensional sketch Ax...
Piotr Indyk, Milan Ruzic