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20152026
most citedHyperLogLogLog: Cardinality Estimation With One Log More

1 citations · 2 across the 5 of their papers we have counts for

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cs.DS2021

DEANN: Speeding up Kernel-Density Estimation using Approximate Nearest Neighbor Search

Matti Karppa, Martin Aumüller, Rasmus Pagh

Kernel Density Estimation (KDE) is a nonparametric method for estimating the shape of a density function, given a set of samples from the distribution. Recently, locality-sensitive…