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» Universal Sparse Modeling
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102
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ICML
2010
IEEE
15 years 1 months ago
Proximal Methods for Sparse Hierarchical Dictionary Learning
We propose to combine two approaches for modeling data admitting sparse representations: on the one hand, dictionary learning has proven effective for various signal processing ta...
Rodolphe Jenatton, Julien Mairal, Guillaume Obozin...
151
Voted
STOC
2006
ACM
244views Algorithms» more  STOC 2006»
16 years 1 months ago
Approximate nearest neighbors and the fast Johnson-Lindenstrauss transform
We introduce a new low-distortion embedding of d 2 into O(log n) p (p = 1, 2), called the Fast-Johnson-LindenstraussTransform. The FJLT is faster than standard random projections ...
Nir Ailon, Bernard Chazelle
CGF
2008
125views more  CGF 2008»
15 years 24 days ago
Sparse points matching by combining 3D mesh saliency with statistical descriptors
This paper proposes new methodology for the detection and matching of salient points over several views of an object. The process is composed by three main phases. In the first st...
Umberto Castellani, Marco Cristani, Simone Fantoni...
113
Voted
FGCS
2006
119views more  FGCS 2006»
15 years 21 days ago
OpenMP versus MPI for PDE solvers based on regular sparse numerical operators
Tw o parallel programming models represented b y OpenMP and MPI are compared for PDE solvers based on regular sparse numerical operators. As a typical representative of such an app...
Markus Nordén, Sverker Holmgren, Michael Th...
ICASSP
2011
IEEE
14 years 4 months ago
Image editing based on Sparse Matrix-Vector multiplication
This paper presents a unified model for image editing in terms of Sparse Matrix-Vector (SpMV) multiplication. In our framework, we cast image editing as a linear energy minimizat...
Ying Wang, Hongping Yan, Chunhong Pan, Shiming Xia...