733 search results - page 28 / 147 » Learning Riemannian Metrics |
KDD
2007
ACM
14 years 9 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...
AAAI
2006
13 years 10 months ago
2006
Learning application-specific distance metrics from labeled data is critical for both statistical classification and information retrieval. Most of the earlier work in this area h...
IJCV
2010
13 years 7 months ago
2010
Abstract Image alignment has been a long standing problem in computer vision. Parameterized Appearance Models (PAMs) such as the Lucas-Kanade method, Eigentracking, and Active Appe...
PR
2010
13 years 7 months ago
2010
Most existing representative works in semi-supervised clustering do not sufficiently solve the violation problem of pairwise constraints. On the other hand, traditional kernel met...
IJCNN
2000
IEEE
14 years 1 months ago
2000
IEEE
We introduce an algorithm for learning a local metric to a continuous input space that measures distances in terms of relevance to the processing task. The relevance is defined a...