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• W2184298032 abstract "In this paper, we survey algorithms for sparse recovery problems that are based on sparse random matrices. Such matrices has several attractive properties: they support algorithms with low computational complexity, and make it easy to perform incremental updates to signals. We discuss applications to several areas, including compressive sensing, data stream computing, and group testing." @default.
• W2184298032 created "2016-06-24" @default.
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• W2184298032 date "2010-01-01" @default.
• W2184298032 modified "2023-09-24" @default.
• W2184298032 title "Sparse Recovery Using Sparse Matrices Significant results in predicting the operation of equipment such as network routers, or the results of group testing for defective items, can often be obtained from a few samples." @default.
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• W2184298032 hasPublicationYear "2010" @default.
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