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Kernel density estimation

topic1 events
papersTODAY 04:00 UTC

Sublinear Sketches for Approximate Nearest Neighbor and Kernel Density Estimation

A revised arXiv paper proposes sublinear sketching techniques for two core machine learning problems: approximate nearest neighbor search and approximate kernel density estimation. The approach targets large-scale data analysis and information retrieval settings where exact computation is impractical, aiming to reduce memory and query costs while preserving accuracy guarantees.

research/nearest-neighbor/sketching/kernel-methods