Semi-supervised classification via discriminative sparse manifold regularization
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- 作者：Zhuang Zhao 476336296@qq.com" class="auth_mail" title="E-mail the corresponding author ; Wei Qi ; Jing Han ; Yi Zhang ; Lian-fa Bai ; blf@njust.edu.cn" class="auth_mail" title="E-mail the corresponding author
- 关键词：Manifold regularization ; Semi-supervised learning ; Classification ; Sparse representation
- 刊名：Signal Processing: Image Communication
- 出版年：2016
- 出版时间：September 2016
- 年：2016
- 卷：47
- 期：Complete
- 页码：207-217
- 全文大小：1408 K
文摘
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We proposed a newly semi-supervised manifold learning algorithm named Discriminative Sparse Manifold Regularization (DSMR) to classify.
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For each labeled or unlabeled sample, its dictionary is updated according to its property and use the new dictionary to reconstruct it.
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Extensive experiments on the several UCI data sets and face data sets demonstrate the effectiveness of the proposed DSMR.