An implementation of Secure Aggregation algorithm based on "Practical Secure Aggregation for Privacy-Preserving Machine Learning (Bonawitz et. al)" in Python.
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Updated
Aug 4, 2019 - Python
An implementation of Secure Aggregation algorithm based on "Practical Secure Aggregation for Privacy-Preserving Machine Learning (Bonawitz et. al)" in Python.
Privacy-Preserving Data Analysis using Pandas
Implementation of the Heflp, a framework enabling practical and overflow-safe federated learning.
Privacy-first decentralized AI training network combining federated learning, blockchain incentives, and quantum-safe cryptography. Enable secure collaborative model development without sharing raw data.
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An implementation of the secure aggregation algorithm for federated learning
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Core federated learning framework for distributed model training with privacy-preserving collaboration.
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