O(n) algorithm found for optimal multinomial Kelly wagering, beating naive O(n log n)
alexbilz · x · 2026-10-16
@octonion reports discovering an O(n) algorithm for optimal multinomial Kelly wagering, improving on the naive O(n log n) approach. He had long suspected such an algorithm existed and describes the result as "not a big deal, but a pleasant discovery." The result is directly relevant to prediction-market betting and portfolio allocation under the Kelly criterion.
More from Research
- Hugging Face launches AI4Science heatmap tracking open models from 79 orgs, AI2 and OpenMed lead — anshulkundaje · 2026-10-16
- MIT's Neil Thompson: AI comes for tasks before jobs, and fixed costs favor big firms — bigdata · 2026-10-16
- UMD's PAIR framework bridges perception and action in VLA models via bridge tokens — Kaixi Feng · 2026-10-16
- CI-MSE offline metric hits -0.87 Spearman correlation with real robot task success vs weak raw MSE — chris_j_paxton · 2026-10-16
- Colossal Biosciences uses AI to decode genetic switches behind the extinct dodo — castrotech · 2026-10-16
- Colossal Biosciences uses AI to identify gene switches in dodo de-extinction push — castrotech · 2026-10-16