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» A Clustering Algorithm Based Absorbing Nearest Neighbors
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CVPR
2005
IEEE
14 years 9 months ago
Applying Neighborhood Consistency for Fast Clustering and Kernel Density Estimation
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...
Kai Zhang, Ming Tang, James T. Kwok
COMPGEOM
2004
ACM
14 years 1 months ago
Locality-sensitive hashing scheme based on p-stable distributions
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 ...
IBPRIA
2009
Springer
14 years 8 days ago
Class Representative Visual Words for Category-Level Object Recognition
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 ...
Roberto Javier López-Sastre, Tinne Tuytelaa...
BMCBI
2011
12 years 11 months ago
Clustering gene expression data with a penalized graph-based metric
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...
Ariel E. Bayá, Pablo M. Granitto
PR
2007
116views more  PR 2007»
13 years 7 months ago
GAPS: A clustering method using a new point symmetry-based distance measure
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...
Sanghamitra Bandyopadhyay, Sriparna Saha