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Differentially Private Asynchronous Federated Learning for Mobile Edge Computing in Urban Informatic
時間 2020-08-08
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differentially
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asynchronous
federated
learning
mobile
edge
computing
urban
informatic
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Differentially Private Asynchronous Federated Learning for Mobile Edge Computing in Urban Informatics閱讀筆記 文獻背景及解決問題 車聯網中的聯邦學習 具體方案 總結與思考 文獻背景及解決問題 因爲無線網絡帶寬和計算資源的限制,車輛很難使用大量數據來進行提升服務質量的機器學習,好比自動駕駛和交通預測
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相關文章
1.
Differentially Private Asynchronous Federated Learning for Mobile Edge Computing in Urban Informatic
2.
論文筆記——Federated learning framework for mobile edge computing networks
3.
Federated Learning in Mobile Edge Networks: AComprehensive Survey(翻譯)
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Deployment Characteristics of "The Edge" in Mobile Edge Computing
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【論文閱讀】Edge Computing Architecture for Mobile Crowdsensing
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