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Mathematical Theories of Machine Learning - Theory and Applications

By Bin Shi
About Mathematical Theories of Machine Learning - Theory and Applications

In the third part, the authors study the problem of subspace clustering with noisy and missing data, which is a problem well-motivated by practical applications data subject to stochastic Gaussian noise and/or incomplete data with uniformly missing entries.

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  • Language:
  • English
  • ISBN:
  • 9783030170783
  • Binding:
  • Paperback
  • Pages:
  • 133
  • Published:
  • August 13, 2020
  • Edition:
  • 12020
  • Dimensions:
  • 155x235x0 mm.
  • Weight:
  • 454 g.
Delivery: 2-4 weeks
Expected delivery: December 20, 2024
Extended return policy to January 30, 2025

Description of Mathematical Theories of Machine Learning - Theory and Applications

In the third part, the authors study the problem of subspace clustering with noisy and missing data, which is a problem well-motivated by practical applications data subject to stochastic Gaussian noise and/or incomplete data with uniformly missing entries.

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