Overview: Enriches understanding of robust feature representations.Explains how to develop robust data mining models.Reinforces robust representation principles with real-world practiceThis book introduces the concepts and models of robust representation learning, and provides a set of solutions to deal with real-world data analytics tasks, such as clustering, classification, time series modeling, outlier detection, collaborative filtering, community detection, etc. Three types of robust feature representations are developed, which extend the understanding of graph, subspace, and dictionary..L
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