【筆記】《Federated Learning With Blockchain for Autonomous Vehicles Analysis and Design Challenges》精讀筆記
論文信息 DOI: 10.1109/TCOMM.2020.2990686 1.摘要 作者提出了基於區塊鏈的聯邦學習（BFL），用於隱私感知和高效的車輛通信網絡。其中自動駕駛車輛車載機器學習（oVML）模型更新以分佈式進行交換和驗證。（與相鄰車輛進行數據交易） 獎勵機制。 開發了一個數學框架：以可控網絡和BFL參數（如：重傳限制、塊大小、塊生成率、幀大小）爲特徵，以便捕捉它們對系統級性能的影
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相關文章
- 1. 【筆記筆記】《Federated Learning With Blockchain for Autonomous Vehicles Analysis and Design Challen》精讀筆記
- 2. 【論文筆記】《FLchain: Federated Learning via MEC-enabled Blockchain Network》精讀筆記
- 3. 論文筆記：Planning and Decision-Making for Autonomous Vehicles
- 4. Federated Learning for Vision-and-Language Grounding Problems閱讀筆記
- 5. Federated Learning with Non-IID Data 論文筆記
- 6. 【論文】《Blockchained On-Device Federated Learning》精讀筆記
- 7. 論文筆記：Securing Data With Blockchain and AI
- 8. Secure Federated Transfer Learning（論文筆記）
- 9. Federated Machine Learning:Concept and Applications(論文筆記)
- 10. 論文筆記——Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge