Scaling laws, tabular data, and actuarial ratemaking models are explored in a real-world motor insurance portfolio
Read the original at arxiv.org→arXiv:2609.03106v1 Announce Type: new Abstract: Scaling laws in modern deep learning describe how held-out loss improves as model capacity, training data, and compute increase, often following power-law trends. We...
Original headline: "Scaling Laws, Tabular Data and Actuarial Ratemaking Models"
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- Sep 4, 04:00 UTC arXiv cs.LG lead source Scaling Laws, Tabular Data and Actuarial Ratemaking Models