publication . Preprint . 2015

Learning Transferable Features with Deep Adaptation Networks

Long, Mingsheng; Cao, Yue; Wang, Jianmin; Jordan, Michael I.;
Open Access English
  • Published: 10 Feb 2015
Abstract
Recent studies reveal that a deep neural network can learn transferable features which generalize well to novel tasks for domain adaptation. However, as deep features eventually transition from general to specific along the network, the feature transferability drops significantly in higher layers with increasing domain discrepancy. Hence, it is important to formally reduce the dataset bias and enhance the transferability in task-specific layers. In this paper, we propose a new Deep Adaptation Network (DAN) architecture, which generalizes deep convolutional neural network to the domain adaptation scenario. In DAN, hidden representations of all task-specific layer...
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free text keywords: Computer Science - Learning
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