Privacy-Preserving Deep Learning: A Comprehensive Survey

In a world increasingly aware of data privacy concerns, this comprehensive survey delves into the evolving field of privacy-preserving deep learning. With contributions from experts Kwangjo Kim and Harry Chandra Tanuwidjaja, the book thoroughly examines foundational concepts, frameworks, and methodologies that safeguard sensitive information while enabling effective machine learning.

The authors explore various techniques that maintain user privacy without sacrificing the performance and accuracy of deep learning models. By presenting a carefully curated selection of studies and applications, the book serves as an essential resource for researchers, practitioners, and students looking to navigate the intricate balance between advanced analytics and ethical data usage in today's digital landscape.