Bilevel model-based discriminative dictionary learning for recognition
Most supervised dictionary learning methods optimize the combinations of reconstruction error, sparsity prior, and discriminative terms. Thus, the learnt dictionaries may not be optimal for recognition tasks. Also, the sparse codes learning models in the training and the testing phases are inconsist...
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Main Authors: | , , |
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Format: | text |
Language: | English |
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Institutional Knowledge at Singapore Management University
2016
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Online Access: | https://ink.library.smu.edu.sg/sis_research/8967 https://ink.library.smu.edu.sg/context/sis_research/article/9970/viewcontent/2016_TIP_bilevel.pdf |
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Institution: | Singapore Management University |
Language: | English |