Findings from University of Technology Sydney Reveals New Findings on Machine Le arning (Blockchain-based Gradient Inversion and Poisoning Defense for Federated Learning)
Findings from University of Technology Sydney Reveals New Findings on Machine Le arning (Blockchain-based Gradient Inversion and Poisoning Defense for Federated Learning)
悉尼理工大学的发现揭示了机器学习（基于区块链的梯度反演和联合学习中毒防御）的新发现
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摘要
机器人与机器学习每日新闻的一位新闻记者兼新闻编辑-机器学习的最新研究结果已经发表。根据来自澳大利亚Ultimo的新闻，B y NewsRx Corporters，研究表明，“Federated Learning(FL)FL已经成为一种有前途的隐私保护机器学习技术，使多个客户能够在不共享原始数据的情况下协作训练全球模型。随着FL在物联网(IoT)场景中越来越多地被采用，对安全和隐私的担忧变得至关重要。”这项研究的财政支持来自澳大利亚研究委员会。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing have been published. According to news originating from Ultimo, Australia, b y NewsRx correspondents, research stated, “Federated learning (FL) FL has emerge d as a promising privacy-preserving machine-learning technology, enabling multip le clients to collaboratively train a global model without sharing raw data. Wit h the increasing adoption of FL in Internet of Things (IoT) scenarios, concerns about security and privacy have become critical.” Financial support for this research came from Australian Research Council.
Key words
Ultimo/Australia/Australia and New Zea land/Cyborgs/Emerging Technologies/Health and Medicine/Machine Learning/Poi soning/University of Technology Sydney
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