From inexact optimization to learning via gradient concentration

no code implementations • 9 Jun 2021 • Bernhard Stankewitz, Nicole Mücke, Lorenzo Rosasco

Optimization in machine learning typically deals with the minimization of empirical objectives defined by training data.

Smoothed residual stopping for statistical inverse problems via truncated SVD estimation

1 code implementation • 30 Sep 2019 • Bernhard Stankewitz

This work examines under what circumstances adaptivity for truncated SVD estimation can be achieved by an early stopping rule based on the smoothed residuals $ \| ( A A^{\top} )^{\alpha / 2} ( Y - A \hat{\mu}^{( m )}) \|^{2} $.

Statistics Theory Statistics Theory 65J20, 62G05