Semi-supervised deep embedded clustering
TL;DR: A new scheme of semi-supervised deep embedded clustering (SDEC) is proposed, which incorporates pairwise constraints in the feature learning process such that data samples belonging to the same cluster are close to each other and data samples belong to different clusters are far away from each other in the learned feature space.
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About: This article is published in Neurocomputing. The article was published on 24 Jan 2019. and is currently open access. The article focuses on the topics: Cluster analysis & Feature learning.
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Citations
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