Adaptive Hypermedia is utilised in several domains, such as eLearning and professional training, where there is a growing movement towards the use of cognitively richer and more `a...
Adapting the classifier trained on a source domain to recognize instances from a new target domain is an important problem that is receiving recent attention. In this paper, we p...
Statistical machine translation is often faced with the problem of combining training data from many diverse sources into a single translation model which then has to translate se...
Majid Razmara, George Foster, Baskaran Sankaran, A...
Domain adaptation refers to the process of adapting an extraction model trained in one domain to another related domain with only unlabeled data. We present a brief survey of exis...
Domain adaptation is a fundamental learning problem where one wishes to use labeled data from one or several source domains to learn a hypothesis performing well on a different, y...