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Privacy-Preserving Machine Learning
book

Privacy-Preserving Machine Learning

by Di Zhuang, Dumindu Samaraweera, Morris Chang
May 2023
Intermediate to advanced content levelIntermediate to advanced
336 pages
10h 3m
English
Manning Publications
Content preview from Privacy-Preserving Machine Learning

9 Compressive privacy for machine learning

This chapter covers

  • Understanding compressive privacy
  • Introducing compressive privacy for machine learning applications
  • Implementing compressive privacy from theory to practice
  • A compressive privacy solution for privacy-preserving machine learning

In previous chapters we’ve looked into differential privacy, local differential privacy, privacy-preserving synthetic data generation, privacy-preserving data mining, and their application when designing privacy-preserving machine learning solutions. As you’ll recall, in differential privacy a trusted data curator collects data from individuals and produces differentially private results by adding precisely computed noise to the aggregation of individuals’ ...

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Publisher Resources

ISBN: 9781617298042Supplemental ContentPublisher SupportOtherPublisher WebsiteSupplemental ContentPurchase Link