Transfer Hashing: From Shallow to Deep.

IEEE Transactions on Neural Networks and Learning Systems(2018)

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摘要
One major assumption used in most existing hashing approaches is that the domain of interest (i.e., the target domain) could provide sufficient training data, either labeled or unlabeled. However, this assumption may be violated in practice. To address this so-called data sparsity issue in hashing, a new framework termed transfer hashing with privileged information (THPI) is proposed, which marria...
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关键词
Quantization (signal),DH-HEMTs,Machine learning,Binary codes,Training,Support vector machines,Learning systems
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