Sparse Recovery Using Sparse Matrices
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 t...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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Institute of Electrical and Electronics Engineers
2012
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| Online Access: | http://hdl.handle.net/1721.1/70932 https://orcid.org/0000-0002-7983-9524 |
| _version_ | 1826205974004760576 |
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| author | Gilbert, Anna Indyk, Piotr |
| author2 | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
| author_facet | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Gilbert, Anna Indyk, Piotr |
| author_sort | Gilbert, Anna |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T13:22:01Z |
| format | Article |
| id | mit-1721.1/70932 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T13:22:01Z |
| publishDate | 2012 |
| publisher | Institute of Electrical and Electronics Engineers |
| record_format | dspace |
| spelling | mit-1721.1/709322022-09-28T13:42:24Z Sparse Recovery Using Sparse Matrices Gilbert, Anna Indyk, Piotr Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Indyk, Piotr Indyk, Piotr 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. Statens naturvidenskabelige forskningsrad (Denmark) Center for Massive Data Algorithmics (MADALGO) David & Lucile Packard Foundation (Fellowship) National Science Foundation (U.S.) (grant CCF-0728645) National Science Foundation (U.S.) (grant CCF-0910765) National Science Foundation (U.S.) (grant DMS-0547744) 2012-05-24T18:31:47Z 2012-05-24T18:31:47Z 2010-06 2009-11 Article http://purl.org/eprint/type/JournalArticle 0018-9219 INSPEC Accession Number: 11304844 http://hdl.handle.net/1721.1/70932 Gilbert, Anna, and Piotr Indyk. “Sparse Recovery Using Sparse Matrices.” Proceedings of the IEEE 98.6 (2010): 937–947. Web. ©2010 IEEE. https://orcid.org/0000-0002-7983-9524 en_US http://dx.doi.org/10.1109/jproc.2010.2045092 Proceedings of the IEEE Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. application/pdf Institute of Electrical and Electronics Engineers IEEE |
| spellingShingle | Gilbert, Anna Indyk, Piotr Sparse Recovery Using Sparse Matrices |
| title | Sparse Recovery Using Sparse Matrices |
| title_full | Sparse Recovery Using Sparse Matrices |
| title_fullStr | Sparse Recovery Using Sparse Matrices |
| title_full_unstemmed | Sparse Recovery Using Sparse Matrices |
| title_short | Sparse Recovery Using Sparse Matrices |
| title_sort | sparse recovery using sparse matrices |
| url | http://hdl.handle.net/1721.1/70932 https://orcid.org/0000-0002-7983-9524 |
| work_keys_str_mv | AT gilbertanna sparserecoveryusingsparsematrices AT indykpiotr sparserecoveryusingsparsematrices |