Orthogonal Matching Pursuit with Noisy and Missing Data: Low and High Dimensional Results

Yudong Chen, Constantine Caramanis

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…