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A Measure-Geometric Theory of Robustness in Machine Learning

arXiv:2610.33123v1 Announce Type: new Abstract: This paper develops a foundational measure-geometric theory of robustness in machine learning. Robustness is formulated as escape from a retained task state relative to a reference measure on a data-bearing manifold, a perturbation gauge, and an admis…

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  1. 2026-10-27 04:00 · arXiv stat.ML
    A Measure-Geometric Theory of Robustness in Machine Learning

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