BriefGPT.xyz
Dec, 2019
具有域自适应的私有联邦学习
Private Federated Learning with Domain Adaptation
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Daniel Peterson, Pallika Kanani, Virendra J. Marathe
TL;DR
本文提出了一种基于联邦学习的机器学习分布式范例，可以在保护隐私的前提下进行多方联合重新训练共享模型，并通过用户级领域自适应来提高模型精度，实验结果表明在为FL模型强制实施差分隐私界限时，该技术可以更大程度地提升模型的准确性。
Abstract
federated learning
(FL) is a
distributed machine learning
(ML) paradigm that enables multiple parties to jointly re-train a shared model without sharing their data with any other parties, offering advantages in b
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