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EMSOFT
2009
Springer
13 years 11 months ago
Modular static scheduling of synchronous data-flow networks: an efficient symbolic representation
This paper addresses the question of producing modular sequential imperative code from synchronous data-flow networks. Precisely, given a system with several input and output flow...
Marc Pouzet, Pascal Raymond
CORR
2008
Springer
98views Education» more  CORR 2008»
13 years 8 months ago
Sparse Recovery by Non-convex Optimization -- Instance Optimality
In this note, we address the theoretical properties of p, a class of compressed sensing decoders that rely on p minimization with p (0, 1) to recover estimates of sparse and compr...
Rayan Saab, Özgür Yilmaz
SIAMSC
2010
215views more  SIAMSC 2010»
13 years 6 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
CORR
2010
Springer
208views Education» more  CORR 2010»
13 years 4 months ago
Real-time Robust Principal Components' Pursuit
In the recent work of Candes et al, the problem of recovering low rank matrix corrupted by i.i.d. sparse outliers is studied and a very elegant solution, principal component pursui...
Chenlu Qiu, Namrata Vaswani
SIAMIS
2011
13 years 2 months ago
Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models
Abstract. Many problems of low-level computer vision and image processing, such as denoising, deconvolution, tomographic reconstruction or superresolution, can be addressed by maxi...
Matthias W. Seeger, Hannes Nickisch