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Explore the concept of differential privacy and its variants in this keynote address delivered by Ilya Mironov from Meta. Delve into information-theoretic methods for trustworthy machine learning as the speaker discusses the importance of privacy preservation in data analysis and machine learning applications. Gain insights into the latest developments and challenges in the field of differential privacy, and understand its implications for building secure and ethical AI systems.
Syllabus
KEYNOTE: Differential Privacy & Variants
Taught by
Simons Institute