Early-stopped gradient descent achieves the minimax-optimal classification error for Gaussian mixtures with label noise under fast-decaying covariance spectra, while interpolating classifiers can be exponentially worse.
Boosting With the L2 Loss.Journal of the American Statistical Associ- ation, 98(462):324–339, 2003
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Minimax Optimal Early-Stopped Gradient Descent for Gaussian Mixture Classification
Early-stopped gradient descent achieves the minimax-optimal classification error for Gaussian mixtures with label noise under fast-decaying covariance spectra, while interpolating classifiers can be exponentially worse.