A new scaling law L(N, D, T) = E + (L0 - E) h/(1+h) with h = a/N^α + b/T^β + c N^γ/D^δ that decomposes loss into undercapacity, undertraining, and overfitting terms and saturates between E and L0.
Data scaling laws for radiology foundation models
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Transfer-aware data allocation derived from observed power-law scaling laws for asymmetric knowledge transfer in 3D medical imaging outperforms standard proportional sampling by up to 58% and generalizes to new budgets.
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Practical Scaling Laws: Converting Compute into Performance in a Data-Constrained World
A new scaling law L(N, D, T) = E + (L0 - E) h/(1+h) with h = a/N^α + b/T^β + c N^γ/D^δ that decomposes loss into undercapacity, undertraining, and overfitting terms and saturates between E and L0.
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Knowledge Transfer Scaling Laws for 3D Medical Imaging
Transfer-aware data allocation derived from observed power-law scaling laws for asymmetric knowledge transfer in 3D medical imaging outperforms standard proportional sampling by up to 58% and generalizes to new budgets.