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- W3084955293 abstract "In the context of gridless sparse optimization, the Sliding Frank Wolfe algorithm recently introduced has shown interesting analytical and practical properties. Nevertheless, is application to large data, such as in the case of 3D deconvolution, is computationally heavy. In this paper, we investigate a strategy for leveraging this burden, in order to make this method more tractable for 3D deconvolution. We show that a boosted SFW can achieve the same results in a significantly reduced amount of time." @default.
- W3084955293 created "2020-09-21" @default.
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- W3084955293 date "2020-09-11" @default.
- W3084955293 modified "2023-09-27" @default.
- W3084955293 title "Boosting the Sliding Frank-Wolfe solver for 3D deconvolution." @default.
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