Multidimensional unstructured sparse recovery via eigenmatrix
<|reference_start|>Multidimensional unstructured sparse recovery via eigenmatrix: This note considers the multidimensional unstructured sparse recovery problems. Examples include Fourier inversion and sparse deconvolution. The eigenmatrix is a data-driven construction with desired approximate eigenvalues and eigenvectors proposed for the one-dimensional problems. This note extends the eigenmatrix approach to multidimensional problems. Numerical results are provided to demonstrate the performance of the proposed method.<|reference_end|>
@article{ying2024multidimensional,
    title={Multidimensional unstructured sparse recovery via eigenmatrix},
    author={Lexing Ying},
    journal={arXiv preprint arXiv:2402.17215},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.17215},
    primaryClass={math.NA cs.LG cs.NA}
}