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» On sparse signal representations
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ICML
2010
IEEE
15 years 7 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
BMVC
2010
15 years 4 months ago
Learning Directional Local Pairwise Bases with Sparse Coding
Recently, sparse coding has been receiving much attention in object and scene recognition tasks because of its superiority in learning an effective codebook over k-means clusterin...
Nobuyuki Morioka, Shin'ichi Satoh
ICASSP
2011
IEEE
14 years 10 months ago
Real-time voice conversion based on instantaneous harmonic parameters
The paper presents a voice conversion framework that can be used in real-time applications. The conversion technique is based on hybrid (deterministic/stochastic) parametric speec...
Elias Azarov, Alexander A. Petrovsky
DATE
2006
IEEE
127views Hardware» more  DATE 2006»
16 years 9 days ago
A signal theory based approach to the statistical analysis of combinatorial nanoelectronic circuits
In this paper we present a method which allows the statistical analysis of nanoelectronic Boolean networks with respect to timing uncertainty and noise. All signals are considered...
Oliver Soffke, Peter Zipf, Tudor Murgan, Manfred G...
CVPR
2009
IEEE
1133views Computer Vision» more  CVPR 2009»
17 years 1 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