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- W4323076621 abstract "We give improved tradeoffs between space and regret for the online learning with expert advice problem over $T$ days with $n$ experts. Given a space budget of $n^{delta}$ for $delta in (0,1)$, we provide an algorithm achieving regret $tilde{O}(n^2 T^{1/(1+delta)})$, improving upon the regret bound $tilde{O}(n^2 T^{2/(2+delta)})$ in the recent work of [PZ23]. The improvement is particularly salient in the regime $delta rightarrow 1$ where the regret of our algorithm approaches $tilde{O}_n(sqrt{T})$, matching the $T$ dependence in the standard online setting without space restrictions." @default.
- W4323076621 created "2023-03-05" @default.
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- W4323076621 date "2023-03-02" @default.
- W4323076621 modified "2023-10-16" @default.
- W4323076621 title "Improved Space Bounds for Learning with Experts" @default.
- W4323076621 doi "https://doi.org/10.48550/arxiv.2303.01453" @default.
- W4323076621 hasPublicationYear "2023" @default.
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