1553 search results - page 11 / 311 » Agnostic Domain Adaptation |
161
Voted
TNN
2011
14 years 10 months ago
2011
Domain adaptation solves a learning problem in a target domain by utilizing the training data in a different but related source domain. Intuitively, discovering a good feature rep...
145
Voted
EMNLP
2009
15 years 1 months ago
2009
Bootstrapping is the process of improving the performance of a trained classifier by iteratively adding data that is labeled by the classifier itself to the training set, and retr...
155
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CICLING
2004
Springer
15 years 7 months ago
2004
Springer
Domain shift is a challenging issue in dialogue management. This paper shows how to extract domain knowledge for dialogue model adaptation. The basic semantic concepts are derived ...
171
Voted
CVPR
2011
IEEE
14 years 11 months ago
2011
IEEE
In real-world applications, “what you saw” during training is often not “what you get” during deployment: the distribution and even the type and dimensionality of features...
140
Voted
ECCV
2010
Springer
15 years 4 months ago
2010
Springer
Abstract. Domain adaptation is an important emerging topic in computer vision. In this paper, we present one of the first studies of domain shift in the context of object recogniti...