In this paper, we propose a novel method for fast nearest neighbors retrieval in non-Euclidean and non-metric spaces. We organize the data into a hierarchical fashion that preserv...
The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
The `kernel approach' has attracted great attention with the development of support vector machine (SVM) and has been studied in a general way. It offers an alternative soluti...
Nearest neighbor (NN) queries have been extended from Euclidean spaces to road networks. Existing approaches are either based on Dijkstra-like network expansion or NN/distance prec...
Abstract. Nearest Neighbor Search (NNS) is employed by many computer vision algorithms. The computational complexity is large and constitutes a challenge for real-time capability. ...