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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2501.18388 |
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| _version_ | 1866910813466394624 |
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| author | Larsen, Kasper Green Mathiasen, Markus Engelund Svendsen, Clement |
| author_facet | Larsen, Kasper Green Mathiasen, Markus Engelund Svendsen, Clement |
| contents | We introduce a new replicable boosting algorithm which significantly improves the sample complexity compared to previous algorithms. The algorithm works by doing two layers of majority voting, using an improved version of the replicable boosting algorithm introduced by Impagliazzo et al. [2022] in the bottom layer. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_18388 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Improved Replicable Boosting with Majority-of-Majorities Larsen, Kasper Green Mathiasen, Markus Engelund Svendsen, Clement Machine Learning We introduce a new replicable boosting algorithm which significantly improves the sample complexity compared to previous algorithms. The algorithm works by doing two layers of majority voting, using an improved version of the replicable boosting algorithm introduced by Impagliazzo et al. [2022] in the bottom layer. |
| title | Improved Replicable Boosting with Majority-of-Majorities |
| topic | Machine Learning |
| url | https://arxiv.org/abs/2501.18388 |