Attributed metadata history
Up to 100 retained publisher events per page for fa2d3df52d963cf3f7fe6b7f3b84137596f78e06b82fbd935420b4b832568235. Withdrawals and unavailable references remain attributed to their publishers.
intelligence_src_7832fd302ddcf52920
observed · 2026-10-12 11:41:03 UTC
available
Fingerprint: 41aab1b8c44b527ca2159cddf8b4e2584fcd901a7a9bfb975ff0ffc04bc5d8ae
intelligence_src_7832fd302ddcf52920
observed · 2026-10-12 11:41:03 UTC
This post is part of a series on privacy-preserving federated learning. The series is a collaboration between NIST and the UK government’s Responsible Technology Adoption Unit (RTA), previously known as the Centre for Data Ethics and Innovation. Learn more and read all the posts published to date at NIST’s Privacy Engineering Collaboration Space or RTA’s blog . Introduction In this post, we talk with Dr. Xiaowei Huang and Dr. Yi Dong (University of Liverpool) and Sikha Pentyala (University of Washington Tacoma), who were winners in the UK-US PETs Prize Challenges . We discuss real-world data
Fingerprint: 7feecbd9530724be6ed1d321705a14ef723189993e854b80d9dd0bac62fb17ac