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Linear quasi-shrinkage estimator for high-dimensional optimization with linear constraints
In large-scale data-driven optimization problems, parameters are often only known approximately due to noisy and small-sized samples. We consider optimization problems with linear constraints where the true parameter matrix is not precisely known, and the number of constraints and variables are both
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