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- W4300696945 abstract "An algorithmic framework to compute sparse or minimal-TV solutions of linear systems is proposed. The framework includes both the Kaczmarz method and the linearized Bregman method as special cases and also several new methods such as a sparse Kaczmarz solver. The algorithmic framework has a variety of applications and is especially useful for problems in which the linear measurements are slow and expensive to obtain. We present examples for online compressed sensing, TV tomographic reconstruction and radio interferometry." @default.
- W4300696945 created "2022-10-04" @default.
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- W4300696945 date "2014-03-28" @default.
- W4300696945 modified "2023-10-16" @default.
- W4300696945 title "A sparse Kaczmarz solver and a linearized Bregman method for online compressed sensing" @default.
- W4300696945 doi "https://doi.org/10.48550/arxiv.1403.7543" @default.
- W4300696945 hasPublicationYear "2014" @default.
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