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Viac informácií o knihe Robust Representation for Data Analytics

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Anotácia knihy

This 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.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.

Parametre knihy

Zaradenie knihy Knihy po anglicky Computing & information technology Computer science Artificial intelligence

• Celý názov: Robust Representation for Data Analytics
• Autor: Sheng Li, Yun Fu
• Jazyk: Angličtina
• Väzba: Pevná
• Počet strán: 224
• EAN: 9783319601755
• ISBN: 331960175X
• ID: 16300673
• Nakladateľ: Springer International Publishing AG
• Hmotnosť: 5221 g
• Rozmery: 235 × 155 × 17 mm
• Dátum vydania: 29. August 2017

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