$p$-adic Manifold Learning and Benchmark Tasks from Impartial Games
Fuente:
arXiv
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| Autor principal: | |
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| Formato: | Preprint |
| Publicado: |
2026
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866911652017864704 |
|---|---|
| author | Mihara, Tomoki |
| author_facet | Mihara, Tomoki |
| contents | We introduce $p$-adic manifold learning, propose an algorithm to solve it, and propose benchmark tasks from impartial games. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_04374 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | $p$-adic Manifold Learning and Benchmark Tasks from Impartial Games Mihara, Tomoki Machine Learning Number Theory We introduce $p$-adic manifold learning, propose an algorithm to solve it, and propose benchmark tasks from impartial games. |
| title | $p$-adic Manifold Learning and Benchmark Tasks from Impartial Games |
| topic | Machine Learning Number Theory |
| url | https://arxiv.org/abs/2605.04374 |