287 search results - page 22 / 58 » Coactive Learning for Distributed Data Mining |
106
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KDD
2009
ACM
15 years 10 months ago
2009
ACM
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
CIKM
2009
Springer
15 years 4 months ago
2009
Springer
Recently there has been increasing interest in the problem of transfer learning, in which the typical assumption that training and testing data are drawn from identical distributi...
109
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KDD
2008
ACM
15 years 10 months ago
2008
ACM
Many time series prediction methods have focused on single step or short term prediction problems due to the inherent difficulty in controlling the propagation of errors from one ...
100
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KDD
2007
ACM
15 years 10 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...
106
click to vote
KDD
2009
ACM
15 years 10 months ago
2009
ACM
When labeled examples are limited and difficult to obtain, transfer learning employs knowledge from a source domain to improve learning accuracy in the target domain. However, the...