Separations and equivalences between turnstile streaming and linear sketching

STOC '20: 52nd Annual ACM SIGACT Symposium on Theory of Computing Chicago IL USA June, 2020(2020)

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摘要
A longstanding observation, which was partially proven by Li, Nguyen, and Woodruff in 2014, and extended by Ai, Hu, Li, and Woodruff in 2016, is that any turnstile streaming algorithm can be implemented as a linear sketch (the reverse is trivially true). We study the relationship between turnstile streaming and linear sketching algorithms in more detail, giving both new separations and new equivalences between the two models. It was shown by Li, Nguyen, and Woodruff in 2014 that, if a turnstile algorithm works for arbitrarily long streams with arbitrarily large coordinates at intermediate stages of the stream, then the turnstile algorithm is equivalent to a linear sketch. We show separations of the opposite form: if either the stream length or the maximum value of the stream are substantially restricted, there exist problems where linear sketching is exponentially harder than turnstile streaming. A further limitation of the Li, Nguyen, and Woodruff equivalence is that the turnstile sketching algorithm is neither explicit nor uniform, but requires an exponentially long advice string. We show how to remove this limitation for deterministic streaming algorithms: we give an explicit small-space algorithm that takes the streaming algorithm and computes an equivalent module.
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关键词
graph algorithms, linear algebra, streaming, sketching, big data, sublinear algorithms
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