14 citations · 17 across the 2 of their papers we have counts for
7 papers
Results of the NeurIPS'21 Challenge on Billion-Scale Approximate Nearest Neighbor Search
Harsha Vardhan Simhadri, George Williams, Martin Aumüller +9
Despite the broad range of algorithms for Approximate Nearest Neighbor Search, most empirical evaluations of algorithms have focused on smaller datasets, typically of 1 million poi…
Differentially Private Sketches for Jaccard Similarity Estimation
Martin Aumüller, Anders Bourgeat, Jana Schmurr
This paper describes two locally-differential private algorithms for releasing user vectors such that the Jaccard similarity between these vectors can be efficiently estimated. The…
The Role of Local Intrinsic Dimensionality in Benchmarking Nearest Neighbor Search
Martin Aumüller, Matteo Ceccarello
This paper reconsiders common benchmarking approaches to nearest neighbor search. It is shown that the concept of local intrinsic dimensionality (LID) allows to choose query sets o…
PUFFINN: Parameterless and Universally Fast FInding of Nearest Neighbors
Martin Aumüller, Tobias Christiani, Rasmus Pagh +1
We present PUFFINN, a parameterless LSH-based index for solving the -nearest neighbor problem with probabilistic guarantees. By parameterless we mean that the user is only requi…
Fair Near Neighbor Search: Independent Range Sampling in High Dimensions
Martin Aumüller, Rasmus Pagh, Francesco Silvestri
Similarity search is a fundamental algorithmic primitive, widely used in many computer science disciplines. There are several variants of the similarity search problem, and one of…
Simple and Fast BlockQuicksort using Lomuto's Partitioning Scheme
Martin Aumüller, Nikolaj Hass
This paper presents simple variants of the BlockQuicksort algorithm described by Edelkamp and Weiss (ESA 2016). The simplification is achieved by using Lomuto's partitioning scheme…