33 search results - page 3 / 7 » Kernel-based distance metric learning for microarray data cl... |
ICMLA
2010
13 years 3 months ago
2010
Gene expression (microarray) data have been used widely in bioinformatics. The expression data of a large number of genes from small numbers of subjects are used to identify inform...
COLT
2010
Springer
13 years 3 months ago
2010
Springer
Recent advances in large-margin classification of data residing in general metric spaces (rather than Hilbert spaces) enable classification under various natural metrics, such as ...
ICML
2007
IEEE
14 years 6 months ago
2007
IEEE
Proportional data (normalized histograms) have been frequently occurring in various areas, and they could be mathematically abstracted as points residing in a geometric simplex. A...
KDD
2008
ACM
14 years 5 months ago
2008
ACM
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
ICML
2007
IEEE
14 years 6 months ago
2007
IEEE
In this paper, we present an information-theoretic approach to learning a Mahalanobis distance function. We formulate the problem as that of minimizing the differential relative e...