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Del i serien Big Data Management

Distributed Machine Learning and Gradient Optimization

Häftad, Engelska, 2023

AvJiawei Jiang,Bin Cui,Ce Zhang

2 219 kr

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This book presents the state of the art in distributed machine learning algorithms that are based on gradient optimization methods. In the big data era, large-scale datasets pose enormous challenges for the existing machine learning systems. As such, implementing machine learning algorithms in a distributed environment has become a key technology, and recent research has shown gradient-based iterative optimization to be an effective solution. Focusing on methods that can speed up large-scale gradient optimization through both algorithm optimizations and careful system implementations, the book introduces three essential techniques in designing a gradient optimization algorithm to train a distributed machine learning model: parallel strategy, data compression and synchronization protocol.Written in a tutorial style, it covers a range of topics, from fundamental knowledge to a number of carefully designed algorithms and systems of distributed machine learning. It will appealto a broad audience in the field of machine learning, artificial intelligence, big data and database management.

Produktinformation

  • Utgivningsdatum2023-02-25
  • Mått155 x 235 x 11 mm
  • Vikt289 g
  • FormatHäftad
  • SpråkEngelska
  • SerieBig Data Management
  • Antal sidor169
  • FörlagSpringer Verlag, Singapore
  • ISBN9789811634222

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