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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2510.25108 |
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| _version_ | 1866918191580577792 |
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| author | Medvedev, Marko Lyu, Kaifeng Li, Zhiyuan Srebro, Nathan |
| author_facet | Medvedev, Marko Lyu, Kaifeng Li, Zhiyuan Srebro, Nathan |
| contents | We consider training and testing on mixture distributions with different training and test proportions. We show that in many settings, and in some sense generically, distribution shift can be beneficial, and test performance can improve due to mismatched training proportions, even if the components are unrelated and with no transfer between components. In a variety of scenarios, we identify the optimal training proportions and the extent to which such distribution shift can be beneficial. We show how the same analysis applies also to a compositional setting with differing distribution of component "skills'' at training and test. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_25108 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Shift is Good: Mismatched Data Mixing Improves Test Performance Medvedev, Marko Lyu, Kaifeng Li, Zhiyuan Srebro, Nathan Machine Learning We consider training and testing on mixture distributions with different training and test proportions. We show that in many settings, and in some sense generically, distribution shift can be beneficial, and test performance can improve due to mismatched training proportions, even if the components are unrelated and with no transfer between components. In a variety of scenarios, we identify the optimal training proportions and the extent to which such distribution shift can be beneficial. We show how the same analysis applies also to a compositional setting with differing distribution of component "skills'' at training and test. |
| title | Shift is Good: Mismatched Data Mixing Improves Test Performance |
| topic | Machine Learning |
| url | https://arxiv.org/abs/2510.25108 |