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- W2810342298 abstract "In the uniformity testing problem, we are given access to samples from some unknown distribution μ on a fixed domain set1,..,n , and our goal is to distinguish the case where μ is the uniform distribution from the case where μ is e-far from uniform in L_1 distance. Centralized uniformity testing has been extensively studied, and it is known that Θ(√ /e^2) samples are necessary and sufficient. In this paper we study distributed uniformity testing : in a network of k nodes, each node i has access to s_i samples from the underlying distribution μ. Our goal is to test uniformity, while minimizing the number of samples per node, as well as the running time. We consider several distributed models: the ŁOCAL model, the CONGEST model, and a 0-round model where nodes cannot communicate with each other at all. We give upper bounds for each model, and a lower bound for the 0-round model. The key to our results is analyzing the centralized uniformity-testing problem in an unusual error regime, for which we give new upper and lower bounds." @default.
- W2810342298 created "2018-07-10" @default.
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- W2810342298 date "2018-07-23" @default.
- W2810342298 modified "2023-10-03" @default.
- W2810342298 title "Distributed Uniformity Testing" @default.
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- W2810342298 doi "https://doi.org/10.1145/3212734.3212772" @default.
- W2810342298 hasPublicationYear "2018" @default.
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