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Supplementary material: Continuation of Nesterov's Smoothing for Regression with Structured Sparsity in High-Dimensional Neuroimaging

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Academic year: 2021

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Figure

Fig 1. The error as a function of the computational time (top plot) and the number of iterations (bottom plot) for different values of τ parameter with the CONESTA solver.
Fig 2. Normalized sum of absolute error (SAE) kXβ k − Xβ ∗ k 1 /kXβ ∗ k 1 as a function of the true precision (red line) and precision estimated with the duality gap (blue line).

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