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ICASSP
2011
IEEE
13 years 17 days ago
Sparse coding and dictionary learning based on the MDL principle
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...
Ignacio Ramírez, Guillermo Sapiro
PAMI
2007
159views more  PAMI 2007»
13 years 8 months ago
Soft Color Segmentation and Its Applications
—We propose an automatic approach to soft color segmentation, which produces soft color segments with an appropriate amount of overlapping and transparency essential to synthesiz...
Yu-Wing Tai, Jiaya Jia, Chi-Keung Tang
HPDC
2007
IEEE
14 years 3 months ago
A statistical approach to risk mitigation in computational markets
We study stochastic models to mitigate the risk of poor Quality-of-Service (QoS) in computational markets. Consumers who purchase services expect both price and performance guaran...
Thomas Sandholm, Kevin Lai
CVPR
2012
IEEE
11 years 11 months ago
The use of on-line co-training to reduce the training set size in pattern recognition methods: Application to left ventricle seg
The use of statistical pattern recognition models to segment the left ventricle of the heart in ultrasound images has gained substantial attention over the last few years. The mai...
Gustavo Carneiro, Jacinto C. Nascimento
CORR
2010
Springer
210views Education» more  CORR 2010»
13 years 9 months ago
Exploiting Statistical Dependencies in Sparse Representations for Signal Recovery
Signal modeling lies at the core of numerous signal and image processing applications. A recent approach that has drawn considerable attention is sparse representation modeling, in...
Tomer Faktor, Yonina C. Eldar, Michael Elad