A λ-convex variational surrogate for shallow NN training yields global well-posedness, almost C³ regularity, and an explicit linear-system solution with 1/α generalization and O(1/N) finite-width rates.
Yihang Chen, Fanghui Liu, Yiping Lu, Grigorios G
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Born Discrete, Made Smooth: Variational Formulation of Shallow Neural Networks
A λ-convex variational surrogate for shallow NN training yields global well-posedness, almost C³ regularity, and an explicit linear-system solution with 1/α generalization and O(1/N) finite-width rates.