mlsanityData to 14 Oct 2026

Distinct Elements in Streams: An Algorithm for the (Text) Book

arXiv 2301.10191 ↗First posted 24 Jan 2023cs.DS cs.DBcited by 1

Not on the map. Why?

Abstract (arXiv)

Given a data stream A = langle a1, a2, ldots, am rangle of m elements where each ai ∈ [n], the Distinct Elements problem is to estimate the number of distinct elements in A.Distinct Elements has been a subject of theoretical and empirical investigations over the past four decades resulting in space optimal algorithms for it.All the current state-of-the-art algorithms are, however, beyond the reach of an undergraduate textbook owing to their reliance on the usage of notions such as pairwise independence and universal hash functions. We present a simple, intuitive, sampling-based space-efficient algorithm whose description and the proof are accessible to undergraduates with the knowledge of basic probability theory.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 24 Jan 2023.

Builds on

No reference list yet.

Built on by

Cited by year

Citing papers per year: 2025: 1.

1 paper.