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The success of deep learning algorithms generally depends on large-scale data, while humans appear to have inherent ability of knowledge transfer, by recognizing and applying relevant knowledge from previous learning experiences when encountering and solving unseen tasks.
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Mask r-cnn
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Unsupervised machine translation using monolingual corpora only
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Revisiting batch normalization for practical domain adaptation
Yanghao Li, Naiyan Wang, Jianping Shi, Jiaying Liu, and Xiaodi Hou · 2017
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Learning multiple visual domains with residual adapters
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Learning from simulated and unsupervised images through adversarial training
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Prototypical networks for few-shot learning
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Deep graph infomax
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