Scalable Semi-Supervised Learning by Efficient Anchor Graph Regularization.

IEEE Transactions on Knowledge and Data Engineering(2016)

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摘要
Many graph-based semi-supervised learning methods for large datasets have been proposed to cope with the rapidly increasing size of data, such as Anchor Graph Regularization (AGR). This model builds a regularization framework by exploring the underlying structure of the whole dataset with both datapoints and anchors. Nevertheless, AGR still has limitations in its two components: (1) in anchor grap...
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关键词
Laplace equations,Semisupervised learning,Estimation,Computational modeling,Computational efficiency,Optimization
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