LREC
2010
13 years 6 months ago
2010
Besides making our thoughts more vivid and filling our communication with richer imagery, metaphor also plays an important structural role in our cognition. Although there is a co...
AUSAI
2008
Springer
13 years 6 months ago
2008
Springer
Traditional text classification algorithms are based on a basic assumption: the training and test data should hold the same distribution. However, this identical distribution assum...
CIKM
2008
Springer
13 years 6 months ago
2008
Springer
In this work we try to bridge the gap often encountered by researchers who find themselves with few or no labeled examples from their desired target domain, yet still have access ...
ATAL
2008
Springer
13 years 6 months ago
2008
Springer
The aim of transfer learning is to accelerate learning in related domains. In reinforcement learning, many different features such as a value function and a policy can be transfer...
AAAI
2007
13 years 6 months ago
2007
Transfer learning addresses the problem of how to leverage knowledge acquired in a source domain to improve the accuracy and speed of learning in a related target domain. This pap...
AAAI
2008
13 years 6 months ago
2008
Transfer learning addresses the problem of how to utilize plenty of labeled data in a source domain to solve related but different problems in a target domain, even when the train...
PKDD
2007
Springer
13 years 10 months ago
2007
Springer
The goal in domain adaptation is to train a model using labeled data sampled from a domain different from the target domain on which the model will be deployed. We exploit unlabel...
CSIE
2009
IEEE
13 years 11 months ago
2009
IEEE
Building a model using machine learning that can classify the sentiment of natural language text often requires an extensive set of labeled training data from the same domain as t...