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In the linear regression model, when the dimension p is fixed and n→∞, the asymptotic distribution of the estimation error for Lasso-type M-estimators is well established. In contrast, the convergence of the discrete structures (patterns) induced by these regularizers, such as sparsity or clustering, has remained largely unaddressed, even for the standard Lasso penalty. Because these lower-di
