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Up to 100 retained publisher events per page for b82a493230329fcf5b6df25a7db277bde9232c1884efef824fdf8889bf76218f. Withdrawals and unavailable references remain attributed to their publishers.

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), Dr. Mat Weldon (UK Office of National Statistics (ONS)), and Sikha Pentyala (University of Washington Tacoma), who were winners in the

Fingerprint: dbc7f6a3b3dddf3b6faa10aefc121c6d6887843a8abd0b0f6d2341ecd6e3c4f8

intelligence_src_7832fd302ddcf52920

observed · 2026-10-12 11:41:03 UTC

available

Fingerprint: 41aab1b8c44b527ca2159cddf8b4e2584fcd901a7a9bfb975ff0ffc04bc5d8ae