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The Formulation of the Structural Risk Minimization Bounds for Deep Learning

    Mathematical statisticians began adapting classical Vapnik-Chervonenkis dimensions to explain why highly overparameterized deep neural networks successfully generalized to new data instead of catastrophically overfitting.

    Part of the 31 AI Roots Facts: 2009 Edition archive. HistoricallyVerified

    Top 5 Structural Foundations: Origins

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