Simona Nemets

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Linear regression with high uncertainties in the measurements, model structure and model permanence is a major challenging problem. Standard regression techniques are based on optimizing a certain performance criterion, usually the mean squared error, and are highly sensitive to uncertainties. Regularization methods have been developed to address the(More)
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