Contraction of Markov Kernels and Differential Privacy - Part I
Offered By: Simons Institute via YouTube
Course Description
Overview
Explore a comprehensive lecture on the contraction of Markov kernels and its connection to differential privacy. Delve into advanced concepts presented by Shahab Asoodeh from McMaster University as part of the Information-Theoretic Methods for Trustworthy Machine Learning series. Gain insights into the mathematical foundations and practical applications of these topics in the field of machine learning and data privacy.
Syllabus
Contraction of Markov kernels and differential privacy (PART I)
Taught by
Simons Institute
Related Courses
Statistical Machine LearningCarnegie Mellon University via Independent Secure and Private AI
Facebook via Udacity Data Privacy and Anonymization in R
DataCamp Build and operate machine learning solutions with Azure Machine Learning
Microsoft via Microsoft Learn Data Privacy and Anonymization in Python
DataCamp