Robust Latent Subspace Learning for Image Classification.

IEEE Transactions on Neural Networks and Learning Systems(2018)

引用 93|浏览83
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摘要
This paper proposes a novel method, called robust latent subspace learning (RLSL), for image classification. We formulate an RLSL problem as a joint optimization problem over both the latent SL and classification model parameter predication, which simultaneously minimizes: 1) the regression loss between the learned data representation and objective outputs and 2) the reconstruction error between t...
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关键词
Robustness,Visualization,Algorithm design and analysis,Optimization,Training,Data models,Principal component analysis
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