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Linear regression in the presence of outliers is an important problem and is challenging as the support of outliers is not known beforehand. Many robust estimators solve this problem via explicitly or implicitly assuming that outliers are sparse and result in large observation errors. We propose an algorithm for robust outlier support identification (AROSI) utilizing a novel objective function with...
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