33 search results - page 3 / 7 » Kernel-based distance metric learning for microarray data cl... |
105
Voted
ICMLA
2010
14 years 8 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...
86
Voted
COLT
2010
Springer
14 years 8 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
15 years 11 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...
122
click to vote
KDD
2008
ACM
15 years 10 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...
82
Voted
ICML
2007
IEEE
15 years 11 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...