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In this paper, the task of robust estimation in the presence of outliers is presented. Outliers are explicitly modeled by employing sparsity arguments. A novel efficient algorithm, based on the greedy Orthogonal Matching Pursuit (OMP) scheme, is derived. Theoretical results concerning the recovery of the solution as well as simulation experiments, which verify the comparative advantages of the new technique, are discussed.