5 search results - page 1 / 1 » A transductive framework of distance metric learning by spec... |
ICML
2007
IEEE
14 years 5 months ago
2007
IEEE
Distance metric learning and nonlinear dimensionality reduction are two interesting and active topics in recent years. However, the connection between them is not thoroughly studi...
BMCBI
2005
13 years 4 months ago
2005
Background: Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks ...
JMLR
2012
11 years 7 months ago
2012
Metric and kernel learning arise in several machine learning applications. However, most existing metric learning algorithms are limited to learning metrics over low-dimensional d...
KDD
2007
ACM
14 years 5 months ago
2007
ACM
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
ICASSP
2010
IEEE
13 years 4 months ago
2010
IEEE
Action recognition is an important but challenging problem in video analytics with a number of solutions proposed to date. However, even if a reliable model for action representat...