On Privacy and Personalization in Federated Learning: A Retrospective on the US/UK PETs Challenge
ML @ CMU
MAY 12, 2023
learning across a handful of data silos such as hospitals or financial institutions) is relatively under-explored, and it presents interesting challenges in terms of how to best model federated data and mitigate privacy risks. If you are feeling adventurous, checkout the extended version of this post with more technical details!
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