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CORR
2011
Springer
210views Education» more  CORR 2011»
14 years 4 months ago
Statistical Compressed Sensing of Gaussian Mixture Models
A novel framework of compressed sensing, namely statistical compressed sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical distribu...
Guoshen Yu, Guillermo Sapiro
CORR
2011
Springer
179views Education» more  CORR 2011»
14 years 4 months ago
An overview of Ciao and its design philosophy
We provide an overall description of the Ciao multiparadigm programming system emphasizing some of the novel aspects and motivations behind its design and implementation. An impor...
Manuel V. Hermenegildo, Francisco Bueno, Manuel Ca...
CORR
2011
Springer
241views Education» more  CORR 2011»
14 years 4 months ago
An Alternating Direction Algorithm for Matrix Completion with Nonnegative Factors
This paper introduces a novel algorithm for the nonnegative matrix factorization and completion problem, which aims to find nonnegative matrices X and Y from a subset of entries o...
Yangyang Xu, Wotao Yin, Zaiwen Wen, Yin Zhang
CORR
2011
Springer
203views Education» more  CORR 2011»
14 years 4 months ago
Robust 1-Bit Compressive Sensing via Binary Stable Embeddings of Sparse Vectors
The Compressive Sensing (CS) framework aims to ease the burden on analog-to-digital converters (ADCs) by reducing the sampling rate required to acquire and stably recover sparse s...
Laurent Jacques, Jason N. Laska, Petros Boufounos,...
CORR
2011
Springer
259views Education» more  CORR 2011»
14 years 4 months ago
The Pros and Cons of Compressive Sensing for Wideband Signal Acquisition: Noise Folding vs. Dynamic Range
Compressive sensing (CS) exploits the sparsity present in many common signals to reduce the number of measurements needed for digital acquisition. With this reduction would come, ...
Mark A. Davenport, Jason N. Laska, John R. Treichl...