1174 search results - page 1 / 235 » Boosting for transfer learning |
ICDM
2009
IEEE
13 years 11 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 5 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 5 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 4 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 5 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...