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» Quantization of Sparse Representations
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147
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ICML
2010
IEEE
15 years 3 months ago
Learning Sparse SVM for Feature Selection on Very High Dimensional Datasets
A sparse representation of Support Vector Machines (SVMs) with respect to input features is desirable for many applications. In this paper, by introducing a 0-1 control variable t...
Mingkui Tan, Li Wang, Ivor W. Tsang
ICML
2010
IEEE
15 years 3 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...
TSP
2011
151views more  TSP 2011»
14 years 9 months ago
Stochastic Models for Sparse and Piecewise-Smooth Signals
Abstract—We introduce an extended family of continuous-domain stochastic models for sparse, piecewise-smooth signals. These are specified as solutions of stochastic differential...
Michael Unser, Pouya Dehghani Tafti
264
Voted
CCIW
2011
Springer
14 years 6 months ago
On the Application of Structured Sparse Model Selection to JPEG Compressed Images
The representation model that considers an image as a sparse linear combination of few atoms of a predefined or learned dictionary has received considerable attention in recent ye...
Giovanni Maria Farinella, Sebastiano Battiato
CVPR
2009
IEEE
1133views Computer Vision» more  CVPR 2009»
16 years 9 months ago
Sparse Subspace Clustering
We propose a method based on sparse representation (SR) to cluster data drawn from multiple low-dimensional linear or affine subspaces embedded in a high-dimensional space. Our ...
Ehsan Elhamifar, René Vidal