1174 search results - page 1 / 235 » Boosting for transfer learning |
ICDM
2009
IEEE
14 years 4 months ago
2009
IEEE
—The success of transfer to improve learning on a target task is highly dependent on the selected source data. Instance-based transfer methods reuse data from the source tasks to...
ICML
2010
IEEE
13 years 10 months ago
2010
IEEE
The goal of transfer learning is to improve the learning of a new target concept given knowledge of related source concept(s). We introduce the first boosting-based algorithms for...
ICML
2007
IEEE
14 years 10 months ago
2007
IEEE
Traditional machine learning makes a basic assumption: the training and test data should be under the same distribution. However, in many cases, this identicaldistribution assumpt...
CVPR
2010
IEEE
13 years 9 months ago
2010
IEEE
Transfer learning allows leveraging the knowledge of source domains, available a priori, to help training a classifier for a target domain, where the available data is scarce. Th...
AAAI
2006
13 years 10 months ago
2006
Many learning tasks in adversarial domains tend to be highly dependent on the opponent. Predefined strategies optimized for play against a specific opponent are not likely to succ...