In nearest neighbor searching we are given a set of n data points in real d-dimensional space, d , and the problem is to preprocess these points into a data structure, so that give...
Many high-profile applications pose high-dimensional nearest-neighbor search problems. Yet, it still remains difficult to achieve fast query times for state-of-the-art approache...
This paper concerns approximate nearest neighbor searching algorithms, which have become increasingly important, especially in high dimensional perception areas such as computer v...
Ting Liu, Andrew W. Moore, Alexander G. Gray, Ke Y...
Classification based on k-nearest neighbors (kNN classification) is one of the most widely used classification methods. The number k of nearest neighbors used for achieving a high ...
In this paper, we develop a general framework for approximate nearest neighbor queries. We categorize the current approaches for nearest neighbor query processing based on either ...