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Martin Aumüller

2 accepted papers

2025

Results of the Big ANN: NeurIPS’23 competition

NeurIPS 2025poster

The 2023 Big ANN Challenge, held at NeurIPS 2023, focused on advancing the state-of-the-art in indexing data structures and search algorithms for practical variants of Approximate Nearest Neighbor (ANN) search that reflect its the growing complexity and diversity of workloads. Unlike prior challenge…

Cited by 0SourcecodeScholar
2022

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

AISTATS 2022poster

Kernel Density Estimation (KDE) is a nonparametric method for estimatig the shape of a density function, given a set of samples from the distribution. Recently, locality-sensitive hashing, originally proposed as a tool for nearest neighbor search, has been shown to enable fast KDE data structures. H…