Budget Allocation for Unknown Value Functions in a Lipschitz Space
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | |
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| _version_ | 1866914100388298752 |
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| author | Bateni, MohammadHossein Esfandiari, Hossein HosseinGhorban, Samira Mirrokni, Alireza Shahdaei, Radin |
| author_facet | Bateni, MohammadHossein Esfandiari, Hossein HosseinGhorban, Samira Mirrokni, Alireza Shahdaei, Radin |
| contents | Building learning models frequently requires evaluating numerous intermediate models. Examples include models considered during feature selection, model structure search, and parameter tunings. The evaluation of an intermediate model influences subsequent model exploration decisions. Although prior knowledge can provide initial quality estimates, true performance is only revealed after evaluation. In this work, we address the challenge of optimally allocating a bounded budget to explore the space of intermediate models. We formalize this as a general budget allocation problem over unknown-value functions within a Lipschitz space. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_10605 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Budget Allocation for Unknown Value Functions in a Lipschitz Space Bateni, MohammadHossein Esfandiari, Hossein HosseinGhorban, Samira Mirrokni, Alireza Shahdaei, Radin Machine Learning Building learning models frequently requires evaluating numerous intermediate models. Examples include models considered during feature selection, model structure search, and parameter tunings. The evaluation of an intermediate model influences subsequent model exploration decisions. Although prior knowledge can provide initial quality estimates, true performance is only revealed after evaluation. In this work, we address the challenge of optimally allocating a bounded budget to explore the space of intermediate models. We formalize this as a general budget allocation problem over unknown-value functions within a Lipschitz space. |
| title | Budget Allocation for Unknown Value Functions in a Lipschitz Space |
| topic | Machine Learning |
| url | https://arxiv.org/abs/2510.10605 |