Depth Improves Training-Time Scaling for Difficult Tasks in Deep Linear Networks
arXiv:2610.35514v1 Announce Type: new Abstract: Neural scaling laws describe the predictable power-law dependence of model performance on training time, dataset size, and model scale, with the exponents quantifying how performance changes with resources. Recent theory has shown how scaling exponent…
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- 2026-10-27 04:00 · arXiv stat.ML
Depth Improves Training-Time Scaling for Difficult Tasks in Deep Linear Networks
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