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» Dictionary learning of convolved signals
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ICASSP
2010
IEEE
14 years 9 months ago
Multiplicative update rules for nonnegative matrix factorization with co-occurrence constraints
Nonnegative matrix factorization (NMF) is a widely-used tool for obtaining low-rank approximations of nonnegative data such as digital images, audio signals, textual data, financ...
Steven K. Tjoa, K. J. Ray Liu
89
Voted
ICCV
2009
IEEE
1318views Computer Vision» more  ICCV 2009»
16 years 2 months ago
Non-Local Sparse Models for Image Restoration
We propose in this paper to unify two different ap- proaches to image restoration: On the one hand, learning a basis set (dictionary) adapted to sparse signal descriptions has p...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
SIGPRO
2011
209views Hardware» more  SIGPRO 2011»
14 years 4 months ago
Surveying and comparing simultaneous sparse approximation (or group-lasso) algorithms
In this paper, we survey and compare different algorithms that, given an overcomplete dictionary of elementary functions, solve the problem of simultaneous sparse signal approxim...
A. Rakotomamonjy
ICASSP
2011
IEEE
14 years 1 months ago
A non-negative approach to semi-supervised separation of speech from noise with the use of temporal dynamics
We present a semi-supervised source separation methodology to denoise speech by modeling speech as one source and noise as the other source. We model speech using the recently pro...
Gautham J. Mysore, Paris Smaragdis
CVPR
2011
IEEE
14 years 5 months ago
Online Detection of Unusual Events in Videos via Dynamic Sparse Coding
Real-time unusual event detection in video stream has been a difficult challenge due to the lack of sufficient training information, volatility of the definitions for both norm...
Bin Zhao, Li Fei-Fei, Eric Xing