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CVPR
2012
IEEE
13 years 2 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 2 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 19 days 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 7 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...
ICASSP
2009
IEEE
15 years 6 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...