733 search results - page 27 / 147 » Learning Riemannian Metrics |
ICML
2003
IEEE
14 years 9 months ago
2003
IEEE
Distance-based methods in machine learning and pattern recognition have to rely on a metric distance between points in the input space. Instead of specifying a metric a priori, we...
CVPR
2008
IEEE
14 years 10 months ago
2008
IEEE
Typical content-based image retrieval (CBIR) solutions with regular Euclidean metric usually cannot achieve satisfactory performance due to the semantic gap challenge. Hence, rele...
KDD
2010
ACM
13 years 10 months ago
2010
ACM
In plenty of scenarios, data can be represented as vectors mathematically abstracted as points in a Euclidean space. Because a great number of machine learning and data mining app...
CVPR
2012
IEEE
11 years 11 months ago
2012
IEEE
Categories in multi-class data are often part of an underlying semantic taxonomy. Recent work in object classification has found interesting ways to use this taxonomy structure t...
ICDM
2009
IEEE
13 years 6 months ago
2009
IEEE
There has been significant recent interest in sparse metric learning (SML) in which we simultaneously learn both a good distance metric and a low-dimensional representation. Unfor...