576 search results - page 22 / 116 » Structured metric learning for high dimensional problems |
PKDD
1999
Springer
13 years 12 months ago
1999
Springer
This paper addresses the problem of learning from highly structured data. Speci cally, it describes a procedure, called decomposition, that allows a learner to access automatically...
JMLR
2010
13 years 2 months ago
2010
We address instance-based learning from a perceptual organization standpoint and present methods for dimensionality estimation, manifold learning and function approximation. Under...
ICCV
1998
IEEE
14 years 9 months ago
1998
IEEE
Proceedings of the 1998 IEEE International Conference on Computer Vision, Bombay, India We introduce a new distance between two distributions that we call the Earth Mover's D...
KDD
2007
ACM
14 years 8 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...
WIRN
2005
Springer
14 years 1 months ago
2005
Springer
We present an algorithmic scheme for unsupervised cluster ensembles, based on randomized projections between metric spaces, by which a substantial dimensionality reduction is obtai...