PPML 2020 - Welcome and Invited Talk - Contributed Talks
Offered By: TheIACR via YouTube
Course Description
Overview
Explore cutting-edge research in privacy-preserving machine learning at the PPML 2020 conference sessions. Begin with an invited talk by Ramesh Raskar from MIT on Split Learning, discussing the benefits of API-style distributed private machine learning among untrusted parties for low power or asynchronous training and inference. Then, delve into four contributed talks covering diverse topics: CrypTFlow2 for practical 2-party secure inference, certifying machine learning models for fairness, crypto-oriented neural architecture design, and privacy-preserving decision tree training and prediction. Gain insights into the latest advancements in secure and privacy-preserving machine learning techniques from leading researchers in the field.
Syllabus
PPML 2020 Session I: Welcome and invited talk and Session II - Contributed Talks
Taught by
TheIACR
Related Courses
Applied CryptographyUniversity of Virginia via Udacity Cryptography II
Stanford University via Coursera Coding the Matrix: Linear Algebra through Computer Science Applications
Brown University via Coursera Cryptography I
Stanford University via Coursera Unpredictable? Randomness, Chance and Free Will
National University of Singapore via Coursera