36 search results - page 2 / 8 » Submodular dictionary learning for sparse coding |
ECCV
2010
Springer
13 years 11 months ago
2010
Springer
Sparse coding of sensory data has recently attracted notable attention in research of learning useful features from the unlabeled data. Empirical studies show that mapping the data...
ICASSP
2010
IEEE
13 years 7 months ago
2010
IEEE
Sparse representation theory has been increasingly used in the fields of signal processing and machine learning. The standard sparse models are not invariant to spatial transform...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
Sparse coding--that is, modelling data vectors as sparse linear combinations of basis elements--is widely used in machine learning, neuroscience, signal processing, and statistics...
ICASSP
2010
IEEE
13 years 5 months ago
2010
IEEE
The enhancement of speech degraded by non-stationary interferers is a highly relevant and difficult task of many signal processing applications. We present a monaural speech enhan...
ICASSP
2011
IEEE
12 years 11 months ago
2011
IEEE
The power of sparse signal coding with learned overcomplete dictionaries has been demonstrated in a variety of applications and fields, from signal processing to statistical infe...