| Presentation | 2012-11-08 Revocery algorithm in compressed sensing based on maximim a posteriori estimation Koujin TAKEDA, Yoshiyuki KABASHIMA, |
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| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | We propose an idea for how to derive sparse data recovery algorithm with smaller computational cost in compressed sensing. It is known that the cost of the standard l_1 recovery algorithm based on linear programming is O(N^3). We show that this cost can be reduced to O(N^2)(for sparse matrix O(N)) by introducing the maximization procedure of posterior. Furthermore, by this method we can reconstruct original data with as small number of observations as possible in principle. We also discuss the relationship between belief-propagation based recovery algorithm in preceding work and our idea. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | compressed sensing / data compression / sparsity / statistical mechanics / maximum a posteriori estimation |
| Paper # | IBISML2012-76 |
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| Conference Information | |
| Committee | IBISML |
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| Conference Date | 2012/10/31(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Registration To | Information-Based Induction Sciences and Machine Learning (IBISML) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Revocery algorithm in compressed sensing based on maximim a posteriori estimation |
| Sub Title (in English) | |
| Keyword(1) | compressed sensing |
| Keyword(2) | data compression |
| Keyword(3) | sparsity |
| Keyword(4) | statistical mechanics |
| Keyword(5) | maximum a posteriori estimation |
| 1st Author's Name | Koujin TAKEDA |
| 1st Author's Affiliation | Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology() |
| 2nd Author's Name | Yoshiyuki KABASHIMA |
| 2nd Author's Affiliation | Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology |
| Date | 2012-11-08 |
| Paper # | IBISML2012-76 |
| Volume (vol) | vol.112 |
| Number (no) | 279 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |