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» Iteratively reweighted algorithms for compressive sensing
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SIAMSC
2010
215views more  SIAMSC 2010»
13 years 4 months ago
A Fast Algorithm for Sparse Reconstruction Based on Shrinkage, Subspace Optimization, and Continuation
We propose a fast algorithm for solving the ℓ1-regularized minimization problem minx∈Rn µ x 1 + Ax − b 2 2 for recovering sparse solutions to an undetermined system of linea...
Zaiwen Wen, Wotao Yin, Donald Goldfarb, Yin Zhang
SIAMIS
2011
13 years 21 days ago
Gradient-Based Methods for Sparse Recovery
The convergence rate is analyzed for the sparse reconstruction by separable approximation (SpaRSA) algorithm for minimizing a sum f(x) + ψ(x), where f is smooth and ψ is convex, ...
William W. Hager, Dzung T. Phan, Hongchao Zhang
ECCV
2008
Springer
14 years 7 months ago
Compressive Structured Light for Recovering Inhomogeneous Participating Media
We propose a new method named compressive structured light for recovering inhomogeneous participating media. Whereas conventional structured light methods emit coded light patterns...
Jinwei Gu, Shree K. Nayar, Eitan Grinspun, Peter N...
ICIP
2009
IEEE
14 years 6 months ago
Monotone Operator Splitting For Optimization Problems In Sparse Recovery
This work focuses on several optimization problems involved in recovery of sparse solutions of linear inverse problems. Such problems appear in many fields including image and sig...
CORR
2010
Springer
153views Education» more  CORR 2010»
13 years 5 months ago
GraphLab: A New Framework for Parallel Machine Learning
Designing and implementing efficient, provably correct parallel machine learning (ML) algorithms is challenging. Existing high-level parallel abstractions like MapReduce are insuf...
Yucheng Low, Joseph Gonzalez, Aapo Kyrola, Danny B...