2245 search results - page 40 / 449 » Metrics that Learn Relevance |
ICML
2003
IEEE
14 years 8 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...
ACE
2004
13 years 9 months ago
2004
In computer science education, the topic of computing theory is one that is commonly not well received by students. Career-oriented students often view the topic as irrelevant, an...
KDD
2010
ACM
13 years 9 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 10 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...
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...