Tight Space Lower Bound for Pseudo-Deterministic Approximate Counting
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arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2023
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| _version_ | 1866909336604770304 |
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| author | Grossman, Ofer Gupta, Meghal Sellke, Mark |
| author_facet | Grossman, Ofer Gupta, Meghal Sellke, Mark |
| contents | We investigate one of the most basic problems in streaming algorithms: approximating the number of elements in the stream. In 1978, Morris famously gave a randomized algorithm achieving a constant-factor approximation error for streams of length at most N in space $O(\log \log N)$. We investigate the pseudo-deterministic complexity of the problem and prove a tight $Ω(\log N)$ lower bound, thus resolving a problem of Goldwasser-Grossman-Mohanty-Woodruff. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2304_01438 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Tight Space Lower Bound for Pseudo-Deterministic Approximate Counting Grossman, Ofer Gupta, Meghal Sellke, Mark Data Structures and Algorithms Computational Complexity We investigate one of the most basic problems in streaming algorithms: approximating the number of elements in the stream. In 1978, Morris famously gave a randomized algorithm achieving a constant-factor approximation error for streams of length at most N in space $O(\log \log N)$. We investigate the pseudo-deterministic complexity of the problem and prove a tight $Ω(\log N)$ lower bound, thus resolving a problem of Goldwasser-Grossman-Mohanty-Woodruff. |
| title | Tight Space Lower Bound for Pseudo-Deterministic Approximate Counting |
| topic | Data Structures and Algorithms Computational Complexity |
| url | https://arxiv.org/abs/2304.01438 |