Federated learning is an emerging machine learning approach that allows the construction of a model between several participants who hold their own private data. This method is secure and privacy-preserving, suitable for training a machine learning model using sensitive data from different sources, such...
Blind over-the-air computation for federated learning Mobile Edge Artificial Intelligence Book2022, Mobile Edge Artificial Intelligence Yuanming Shi, ... Yong Zhou Explore book 10.1 Blind over-the-air computation Although over-the-air computation presents great promise for facilitating model aggregation ...
Federated learning (FL) is a popular privacy-preserving edge-to-cloud technique used for training and deploying artificial intelligence (AI) models on edge... E Gronberg,L D'Aliberti,M Saebo,... 被引量: 0发表: 2025年 Light Blind: Why Encrypt If You Can Partition? This paper focuses on ...
A multifaceted survey on privacy preservation of federated learning: progress, challenges, and opportunities Sanchita Saha Ashlesha Hota Sukumar Nandi Artificial Intelligence Review(2024) Leveraging Grover’s Algorithm for Quantum Searchable Encryption in Cloud Infrastructure and its application in AES Resourc...
Mastodon I won’t go into the details of federated social and how Mastodon is structured. Instead, I want to talk about what it feels like and what it inspires. Using Mastodon is like going back to the early days of social. I was a big fan of FriendFeed, a social platform that most...
One of the first initiatives was an experimental tracking feature, Federated Learning of Cohorts (FLoC), which enables interest-based advertising by creating user profiles or “cohorts” without revealing user identities. Recently, Topics, an initiative to preserve privacy while allowing publishers to ...