Explore the second part of a lecture on the contraction of Markov kernels and differential privacy, presented by Mario Diaz from the Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas (IIMAS). Delve into advanced concepts within the field of information-theoretic methods for trustworthy machine learning. This 34-minute talk, hosted by the Simons Institute, offers a deep dive into the mathematical foundations and applications of these crucial topics in modern data science and privacy-preserving algorithms.
Contraction of Markov Kernels and Differential Privacy - Part II
Overview
Syllabus
Contraction of Markov Kernels and Differential Privacy (PART II)
Taught by
Simons Institute
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Contraction of Markov Kernels and Differential Privacy - Part I
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