80 search results - page 7 / 16 » Adaptive Distance Metric Learning for Clustering |
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
The performance of graph based clustering methods critically depends on the quality of the distance function, used to compute similarities between pairs of neighboring nodes. In t...
ICML
2007
IEEE
14 years 8 months ago
2007
IEEE
The k-Nearest Neighbors algorithm can be easily adapted to classify complex objects (e.g. sets, graphs) as long as a proper dissimilarity function is given over an input space. Bo...
ICCV
2007
IEEE
14 years 9 months ago
2007
IEEE
In this paper, we propose a novel metric learning method based on regularized moving least squares. Unlike most previous metric learning methods which learn a global Mahalanobis d...
NIPS
2004
13 years 8 months ago
2004
Various problems in machine learning, databases, and statistics involve pairwise distances among a set of objects. It is often desirable for these distances to satisfy the propert...
BMCBI
2011
12 years 11 months ago
2011
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...