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Influence Diagnostics in High-dimensional M-estimation: Precise Asymptotics
The impact of a given training point on a statistical model can be measured through its leave-one-out influence on the model parameters, which quantifies how its removal from the training set affects the learned weights. For convex M-estimation under Gaussian design, in the high-dimensional limit $n
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