An unbalanced optimal transport framework for histogram-valued regression with applications to sports analytics
Abstract This paper develops a regression framework for histogram-valued data using unbalanced optimal transport. By generalizing classical optimal transport theory to account for mass imbalances, the proposed methodology operates within the space of non-negative measures, offering a more flexible a...
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| Format: | Artigo |
| Jezik: | Inglês |
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SpringerOpen
2026-02-01
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| Serija: | Journal of Big Data |
| Teme: | |
| Online dostop: | https://doi.org/10.1186/s40537-026-01388-7 |
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