Tight Space Lower Bound for Pseudo-Deterministic Approximate Counting
Ofer Grossman, Meghal Gupta, Mark Sellke
2023Year
1Citations
Abstract
We investigate one of the most basic problems in streaming algorithms: approximating the number of elements in the stream. Famously, [Mor78] gave a randomized algorithm achieving a constant-factor approximation error for streams of length at most N in space . We investigate the pseudo-deterministic complexity of the problem and prove a tight lower bound, thus resolving a problem of [GGMW20].
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