A Short Note on a Variant of the Squint Algorithm
Fuente:
arXiv
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866914367690244096 |
|---|---|
| author | Luo, Haipeng |
| author_facet | Luo, Haipeng |
| contents | This short note describes a simple variant of the Squint algorithm of Koolen and Van Erven [2015] for the classic expert problem. Via an equally simple modification of their proof, we prove that this variant ensures a regret bound that resembles the one shown in a recent work by Freund et al. [2026] for a variant of the NormalHedge algorithm [Chaudhuri et al., 2009]. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_03409 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A Short Note on a Variant of the Squint Algorithm Luo, Haipeng Machine Learning This short note describes a simple variant of the Squint algorithm of Koolen and Van Erven [2015] for the classic expert problem. Via an equally simple modification of their proof, we prove that this variant ensures a regret bound that resembles the one shown in a recent work by Freund et al. [2026] for a variant of the NormalHedge algorithm [Chaudhuri et al., 2009]. |
| title | A Short Note on a Variant of the Squint Algorithm |
| topic | Machine Learning |
| url | https://arxiv.org/abs/2603.03409 |