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A Randomized Algorithm for Sparse Recovery

2020 25th International Conference on Pattern Recognition (ICPR), 2021
This paper considers the problem of sparse signal recovery where there is a structure in the signal. Efficient recovery schemes can be designed to leverage the signal structure. Following the model-based compressive sensing framework, we have developed an efficient algorithm for both head and tail approximations for the model-projection problem.
Huiyuan Yu, Maggie X. Cheng, Yingdong Lu
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