A Theory of Generalization in Deep Learning: Dynamics of Neural Tangent Kernels

The article explores why deep learning works by re-examining the bias-variance tradeoff, introducing concepts like benign overfitting and double descent, and proposes a dynamic framework based on the empirical Neural Tangent Kernel (eNTK) to explain generalization.

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