Space and time efficient kernel density estimation in high dimensions

Recently, Charikar and Siminelakis (2017) presented a framework for kernel density estimation in provably sublinear query time, for kernels that possess a certain hashing-based property. However, their data structure requires a significantly increased super-linear storage space, as well as super-lin...

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Bibliographic Details
Main Authors: Indyk, Piotr, Wagner, Tal
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Format: Article
Language:English
Published: Morgan Kaufmann Publishers 2021
Online Access:https://hdl.handle.net/1721.1/129407