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» Sparse Image Reconstruction using Sparse Priors
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CORR
2011
Springer
179views Education» more  CORR 2011»
14 years 9 months ago
Sparsity based sub-wavelength imaging with partially incoherent light via quadratic compressed sensing
: We demonstrate that sub-wavelength optical images borne on partially-spatially-incoherent light can be recovered, from their far-field or from the blurred image, given the prior ...
Yoav Shechtman, Yonina C. Eldar, Alexander Szameit...
ISBI
2009
IEEE
16 years 6 days ago
Improving M/EEG Source Localization with an Inter-Condition Sparse Prior
The inverse problem with distributed dipoles models in M/EEG is strongly ill-posed requiring to set priors on the solution. Most common priors are based on a convenient ℓ2 norm....
Alexandre Gramfort, Matthieu Kowalski
JMLR
2010
202views more  JMLR 2010»
15 years 6 days ago
Learning the Structure of Deep Sparse Graphical Models
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...
ICASSP
2011
IEEE
14 years 9 months ago
Covariate-dependent dictionary learning and sparse coding
A dependent hierarchical beta process (dHBP) is developed as a prior for data that may be represented in terms of a sparse set of latent features (dictionary elements), with covar...
Mingyuan Zhou, Hongxia Yang, Guillermo Sapiro, Dav...
CVPR
2010
IEEE
16 years 1 months ago
High-Resolution Modeling of Moving and Deforming Objects Using Sparse Geometric and Dense Photometric Measurements
Modeling moving and deforming objects requires capturing as much information as possible during a very short time. When using off-the-shelf hardware, this often hinders the resolu...
Yi Xu, Daniel Aliaga