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Robust Representation for Data Analytics: Models and Applications

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  • Дата: 25-03-2018, 08:04
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Название: Robust Representation for Data Analytics: Models and Applications
Автор: Sheng Li, Yun Fu
Издательство: Springer
Год: 2017
ISBN: 9783319601762
Серия: Advanced Information and Knowledge Processing
Формат: epub
Страниц: 224
Размер: 5,4 mb
Язык: English

Three types of robust feature representations are developed, which extend the understanding of graph, subspace, and dictionary.

Leveraging the theory of low-rank and sparse modeling, the authors develop robust feature representations under various learning paradigms, including unsupervised learning, supervised learning, semi-supervised learning, multi-view learning, transfer learning, and deep learning. Robust Representations for Data Analytics covers a wide range of applications in the research fields of big data, human-centered computing, pattern recognition, digital marketing, web mining, and computer vision.












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