Abstract. We consider approximate nearest neighbor searching in metric spaces of constant doubling dimension. More formally, we are given a set S of n points and an error bound &g...
Sunil Arya, David M. Mount, Antoine Vigneron, Jian...
Current advances in chip design and manufacturing have allowed IC manufacturing to approach the nanometer range. As the feature size scales down, greater variability is experience...
When searching databases of nucleotide or protein sequences, finding a local alignment of two sequences is one of the main tasks. Since the sizes of available databases grow const...
Although clustering under constraints is a current research topic, a hierarchical setting, in which a hierarchy of clusters is the goal, is usually not considered. This paper trie...
Many machine learning algorithms for clustering or dimensionality reduction take as input a cloud of points in Euclidean space, and construct a graph with the input data points as...