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Reconstruction of jointly sparse vectors via manifold optimization

Year: 2019
Type: article
DOI: 10.1016/j.apnum.2019.05.022
Language: English
Open Access status: bronze
Funders: National Science Foundation, U.S. Department of Energy, Battelle, UT-Battelle, Office of Science, Division of Mathematical Sciences, Advanced Scientific Computing Research, Oak Ridge National Laboratory
Awards: G1026679911, G121915436, G1286236842, G1645119126, G166562317, G1799333409, G1863003419, G203625172, G2411683797, G2487984123, G2757267231, G2988778103, G3083819904, G3136028036, G313676650, G3809081345, G3945850812, G419881185, G42916606, G4423657506, G4501827968, G498139845, G5726405315, G6004296295, G6344208662, Collaborative Research: Mathematical Methods for Optimal Polynomial Recovery of High-Dimensional Systems from Sparse and Noisy Data, G660579501, G6652958823, G675320460, G8269158468, G8906985441, G8943143067, G969889393
OpenAlex ID: W2900508686
FWCI: 0.611
Cites: 45
Cited by: 6
Related to: 10