PPML 2020 - Welcome and Invited Talk - Contributed Talks

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.