International audienceWe compare the performance of three nearest neighbor search algorithms: the Orchard, ball tree, and VP-tree algorithms. These algorithms are commonly used for nearest-neighbor searches and are known for their efficiency in large datasets. We analyze the fraction of distances computed in relation to the size of the dataset and its dimension. For each algorithm we derive a fitting function for the efficiency as a function to set size and dimension. The article aims to provide a comprehensive analysis of the performance of these algorithms and help researchers and practitioners choose the best algorithm for their specific application
In this paper, we present a new cost model for nearest neighbor search in high-dimensional data spac...
The long-standing problem of efficient nearest-neighbor (NN) search has ubiqui-tous applications ran...
Affordable, fast computers with large memories have lessened the demand for program efficiency, but ...
International audienceWe compare the performance of three nearest neighbor search algorithms: the Or...
In many computer vision problems, answering the nearest neighbor queries efficiently, especially in ...
Abstract. Choosing which fast Nearest Neighbour search algorithm to use depends on the task we face....
This paper reconsiders common benchmarking approaches to nearest neighbor search. It is shown that t...
Approximate Nearest neighbor search (ANNS) is fundamental and essential operation in applications f...
AbstractÐA new fast nearest-neighbor algorithm is described that uses principal component analysis t...
Nearest-neighbor search is a very natural and universal problem in computer science. Often times, th...
In this paper, we present a fast and versatile algorithm which can rapidly perform a variety of near...
We consider the task of nearest-neighbor search with the class of binary-space-partitioning trees, w...
We consider the task of nearest-neighbor search with the class of binary-space-partitioning trees, w...
Given n data points in d-dimensional space, nearest-neighbor searching involves determining the near...
Choosing which fast Nearest Neighbour search algorithm to use depends on the task we face. Usually k...
In this paper, we present a new cost model for nearest neighbor search in high-dimensional data spac...
The long-standing problem of efficient nearest-neighbor (NN) search has ubiqui-tous applications ran...
Affordable, fast computers with large memories have lessened the demand for program efficiency, but ...
International audienceWe compare the performance of three nearest neighbor search algorithms: the Or...
In many computer vision problems, answering the nearest neighbor queries efficiently, especially in ...
Abstract. Choosing which fast Nearest Neighbour search algorithm to use depends on the task we face....
This paper reconsiders common benchmarking approaches to nearest neighbor search. It is shown that t...
Approximate Nearest neighbor search (ANNS) is fundamental and essential operation in applications f...
AbstractÐA new fast nearest-neighbor algorithm is described that uses principal component analysis t...
Nearest-neighbor search is a very natural and universal problem in computer science. Often times, th...
In this paper, we present a fast and versatile algorithm which can rapidly perform a variety of near...
We consider the task of nearest-neighbor search with the class of binary-space-partitioning trees, w...
We consider the task of nearest-neighbor search with the class of binary-space-partitioning trees, w...
Given n data points in d-dimensional space, nearest-neighbor searching involves determining the near...
Choosing which fast Nearest Neighbour search algorithm to use depends on the task we face. Usually k...
In this paper, we present a new cost model for nearest neighbor search in high-dimensional data spac...
The long-standing problem of efficient nearest-neighbor (NN) search has ubiqui-tous applications ran...
Affordable, fast computers with large memories have lessened the demand for program efficiency, but ...