bokomslag Robust Representation for Data Analytics
Data & IT

Robust Representation for Data Analytics

Sheng Li Yun Fu

Pocket

1819:-

Funktionen begränsas av dina webbläsarinställningar (t.ex. privat läge).

Uppskattad leveranstid 10-15 arbetsdagar

Fri frakt för medlemmar vid köp för minst 249:-

Andra format:

  • 224 sidor
  • 2018
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.
  • Författare: Sheng Li, Yun Fu
  • Format: Pocket/Paperback
  • ISBN: 9783319867960
  • Språk: Engelska
  • Antal sidor: 224
  • Utgivningsdatum: 2018-08-04
  • Förlag: Springer International Publishing AG