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309
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CVPR
2012
IEEE
13 years 6 months ago
See all by looking at a few: Sparse modeling for finding representative objects
We consider the problem of finding a few representatives for a dataset, i.e., a subset of data points that efficiently describes the entire dataset. We assume that each data poi...
Ehsan Elhamifar, Guillermo Sapiro, René Vid...
CVPR
2012
IEEE
13 years 6 months ago
Submodular dictionary learning for sparse coding
A greedy-based approach to learn a compact and discriminative dictionary for sparse representation is presented. We propose an objective function consisting of two components: ent...
Zhuolin Jiang, Guangxiao Zhang, Larry S. Davis
ICML
2007
IEEE
16 years 4 months ago
Full regularization path for sparse principal component analysis
Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a particular linear combination of the input variables while constraining the numb...
Alexandre d'Aspremont, Francis R. Bach, Laurent El...
CORR
2012
Springer
232views Education» more  CORR 2012»
13 years 11 months ago
Smoothing Proximal Gradient Method for General Structured Sparse Learning
We study the problem of learning high dimensional regression models regularized by a structured-sparsity-inducing penalty that encodes prior structural information on either input...
Xi Chen, Qihang Lin, Seyoung Kim, Jaime G. Carbone...
135
Voted
ICASSP
2009
IEEE
15 years 10 months ago
Robust speech dereverberation based on non-negativity and sparse nature of speech spectrograms
This paper presents a blind dereverberation method designed to recover the subband envelope of an original speech signal from its reverberant version. The problem is formulated as...
Hirokazu Kameoka, Tomohiro Nakatani, Takuya Yoshio...