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Orthogonal Matching Pursuit with Noisy and Missing Data: Low and High Dimensional Results
Orthogonal Matching Pursuit Noisy and Missing Data High Dimensional Results Statistics Theory
2012/6/21
Many models for sparse regression typically assume that the covariates are known completely, and without noise. Particularly in high-dimensional applications, this is often not the case. This paper de...