Nearest neighborhood consistency is an important concept in statistical pattern recognition, which underlies the well-known k-nearest neighbor method. In this paper, we combine th...
We present a novel Locality-Sensitive Hashing scheme for the Approximate Nearest Neighbor Problem under ÐÔ norm, based on Ôstable distributions. Our scheme improves the running...
Mayur Datar, Nicole Immorlica, Piotr Indyk, Vahab ...
Recent works in object recognition often use visual words, i.e. vector quantized local descriptors extracted from the images. In this paper we present a novel method to build such ...
Background: The search for cluster structure in microarray datasets is a base problem for the so-called “-omic sciences”. A difficult problem in clustering is how to handle da...
In this paper, an evolutionary clustering technique is described that uses a new point symmetry-based distance measure. The algorithm is therefore able to detect both convex and n...