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Minimum Variance Estimation of a Sparse Vector Within the Linear Gaussian Model: An RKHS Approach.

, , , , and . IEEE Trans. Inf. Theory, 60 (10): 6555-6575 (2014)

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The Cramer-Rao Bound for Sparse Estimation., and . CoRR, (2009)Unbiased Estimation of a Sparse Vector in White Gaussian Noise., , , and . IEEE Trans. Inf. Theory, 57 (12): 7856-7876 (2011)Coherence-based performance guarantees for estimating a sparse vector under random noise., , and . IEEE Trans. Signal Process., 58 (10): 5030-5043 (2010)Near-Oracle Performance of Greedy Block-Sparse Estimation Techniques From Noisy Measurements., and . J. Sel. Topics Signal Processing, 5 (5): 1032-1047 (2011)Coherence-based near-oracle performance guarantees for sparse estimation under Gaussian noise., , and . ICASSP, page 3590-3593. IEEE, (2010)Minimum Variance Estimation of a Sparse Vector Within the Linear Gaussian Model: An RKHS Approach., , , , and . IEEE Trans. Inf. Theory, 60 (10): 6555-6575 (2014)Minimax estimators dominating the least-squares estimator., and . ICASSP (4), page 53-56. IEEE, (2005)On unbiased estimation of sparse vectors corrupted by Gaussian noise., , , and . ICASSP, page 3990-3993. IEEE, (2010)On the Constrained CramÉr-Rao Bound With a Singular Fisher Information Matrix., and . IEEE Signal Process. Lett., 16 (6): 453-456 (2009)Physics-Aware Downsampling with Deep Learning for Scalable Flood Modeling., , , , and . NeurIPS, page 1378-1389. (2021)