18 citations · 70 across the 15 of their papers we have counts for
3 papers · 1 filter
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…