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  1. [1802.08464] The geometry of off-the-grid compressed sensing

  2. The Geometry of Off-the-Grid Compressed Sensing | Foundations …

  3. The Geometry of Off-the-Grid Compressed Sensing | Request PDF

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    The first work in this compressed sensing direction is by Tang et al [ 55] where they showed that the recovery guarantees of [ 15] remain valid with high probability when only a small number of (Fourier) measurements are randomly selected, of the order (up to log factors) of the sparsity of the underlying measure.
    This is a "continuous", often called off-the-grid, extension of the compressed sensing problem, where the ℓ1 norm is replaced by the total variation of measures. This extension is appealing from a numerical perspective because it avoids to discretize the the space by some grid.
    Successful examples of applications of such “off-the-grid methods” include single-molecule fluorescent imaging [ 8 ], spikes sorting in neurosciences [ 33 ], mixture model estimation [ 37] and training shallow neural networks [ 5 ].
    This is achieved by extending the so-called golfing scheme [ 16, 39] to the infinite-dimensional setting. At the heart of this result is the definition of an intrinsic distance over the parameter domain, the so-called Fisher geodesic distance.
  5. The Geometry of Off-the-Grid Compressed Sensing

  6. The geometry of off-the-grid compressed sensing

  7. The geometry of off-the-grid compressed sensing - Papers With …

  8. Compressed Sensing Off the Grid | IEEE Journals & Magazine | IEEE …

  9. ‪Clarice Poon‬ - ‪Google Scholar‬