Simpler Distribution Testing with Little Memory
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Abstract (arXiv)
We consider the question of distribution testing (specifically, uniformity and closeness testing) in the streaming setting, ie under stringent memory constraints. We improve on the results of Diakonikolas, Gouleakis, Kane, and Rao (2019) by providing considerably simpler algorithms, which remove some restrictions on the range of parameters and match their lower bounds.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). First posted on arXiv 2 Nov 2023.
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Citing papers per year: 2023: 1.
1 paper.
- 2023Statistical Inference with Limited Memory: A Surveycited by 1
- 2023Statistical Inference with Limited Memory: A Survey23 Dec 2023