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Natalie Durgin, Rachel Grotheer, Chenxi Huang, Shuang Li, Anna Ma, Deanna Needell, Jing Qin |
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A Simple Recovery Framework for Signals with Time-Varying Sparse Support |
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Advances in Data Science. AWM Series, vol 26. Springer, 2021. |
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Jing Qin, Shuang Li, Deanna Needell, Anna Ma, Rachel Grotheer, Chenxi Huang, Natalie Durgin |
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Stochastic Greedy Algorithms For Multiple Measurement Vectors |
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Inverse Problems and Imaging, vol. 15, Num. 1, pp. 79-107, 2021. |
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Natalie Durgin, Rachel Grotheer, Chenxi Huang, Shuang Li, Anna Ma, Deanna Needell, Jing Qin |
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Jointly Sparse Signal Recovery with Prior Information |
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Proc. Asilomar Conference on Signals, Systems, and Computers Nov. 2019 |
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Natalie Durgin, Rachel Grotheer, Chenxi Huang, Shuang Li, Anna Ma, Deanna Needell, Jing Qin |
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Fast Hyperspectral Diffuse Optical Imaging Method with Joint Sparsity |
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IEEE Engineering in Medicine and Biology Society (EMBC). IEEE. 2019, pp. 4758–4761. |
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Natalie Durgin, Rachel Grotheer, Chenxi Huang, Shuang Li, Anna Ma, Deanna Needell, Jing Qin |
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Compressed Anomaly Detection with Multiple Mixed Observations |
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Research in Data Science. AWM Series, vol 17. Springer, 2019, pp. 211-237. |
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Natalie Durgin, Rachel Grotheer, Chenxi Huang, Shuang Li, Anna Ma, Deanna Needell, Jing Qin |
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Sparse Randomized Kaczmarz for Support Recovery of Jointly Sparse Corrupted Multiple Measurement Vectors |
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Research in Data Science. AWM Series, vol 17. Springer, 2019 |