14 citations · 17 across the 5 of their papers we have counts for
4 papers · 1 filter
Differentially Private High-Dimensional Approximate Range Counting, Revisited
Martin Aumüller, Fabrizio Boninsegna, Francesco Silvestri
Locality Sensitive Filters are known for offering a quasi-linear space data structure with rigorous guarantees for the Approximate Near Neighbor search (ANN) problem. Building on L…
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…