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» On sparse signal representations
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TIP
2011
255views more  TIP 2011»
15 years 29 days ago
Dictionary Learning for Stereo Image Representation
—One of the major challenges in multi-view imaging is the definition of a representation that reveals the intrinsic geometry of the visual information. Sparse image representati...
Ivana Tosic, Pascal Frossard
202
Voted
MTV
2007
IEEE
166views Hardware» more  MTV 2007»
16 years 9 days ago
Application of Automated Model Generation Techniques to Analog/Mixed-Signal Circuits
Abstract—Abstract models of analog/mixed-signal (AMS) circuits can be used for formal verification and system-level simulation. The difficulty of creating these models preclude...
Scott Little, Alper Sen, Chris J. Myers
CVPR
2011
IEEE
14 years 9 months ago
A Non-convex Relaxation Approach to Sparse Dictionary Learning
Dictionary learning is a challenging theme in computer vision. The basic goal is to learn a sparse representation from an overcomplete basis set. Most existing approaches employ a...
Jianping Shi, Xiang Ren, Jingdong Wang, Guang Dai,...
CORR
2012
Springer
225views Education» more  CORR 2012»
14 years 1 months ago
Compressive Principal Component Pursuit
We consider the problem of recovering a target matrix that is a superposition of low-rank and sparse components, from a small set of linear measurements. This problem arises in co...
John Wright, Arvind Ganesh, Kerui Min, Yi Ma
CORR
2011
Springer
152views Education» more  CORR 2011»
15 years 1 months ago
Sparsity Equivalence of Anisotropic Decompositions
Anisotropic decompositions using representation systems such as curvelets, contourlet, or shearlets have recently attracted significantly increased attention due to the fact that...
Gitta Kutyniok