In the linear-width regime, the second GD step yields a spiked random matrix whose number of outliers is floor(alpha2 / (1/2 - alpha1)), and batch reuse enables learning directions with information exponent greater than one under suitable alpha scalings.
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2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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CASA achieves 93.9% slide-level accuracy on Camelyon17-WILDS by adversarially augmenting stains in Macenko space with DKW-calibrated coverage, outperforming baselines including in worst-group accuracy.
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Feature Learning in Linear-Width Two-Layer Networks: Two vs. One Step of Gradient Descent
In the linear-width regime, the second GD step yields a spiked random matrix whose number of outliers is floor(alpha2 / (1/2 - alpha1)), and batch reuse enables learning directions with information exponent greater than one under suitable alpha scalings.
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Physics-Grounded Adversarial Stain Augmentation with Calibrated Coverage Guarantees
CASA achieves 93.9% slide-level accuracy on Camelyon17-WILDS by adversarially augmenting stains in Macenko space with DKW-calibrated coverage, outperforming baselines including in worst-group accuracy.