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.