Communication Resources Constrained Hierarchical Federated Learning for End-to-End Autonomous Driving

Documenti analoghi

• pFedLVM: A Large Vision Model (LVM)-Driven and Latent Feature-Based Personalized Federated Learning Framework in Autonomous Driving
  di: Kou, Wei-Bin, et al.
  Pubblicazione: (2024)
• Sense4FL: Vehicular Crowdsensing Enhanced Federated Learning for Object Detection in Autonomous Driving
  di: Ma, Yanan, et al.
  Pubblicazione: (2025)
• Communication-and-Computation Efficient Split Federated Learning: Gradient Aggregation and Resource Management
  di: Liang, Yipeng, et al.
  Pubblicazione: (2025)
• Digital Twins in the Cloud: A Modular, Scalable and Interoperable Framework for Accelerating Verification and Validation of Autonomous Driving Solutions
  di: Samak, Tanmay Vilas, et al.
  Pubblicazione: (2025)
• FeedSign: Robust Full-parameter Federated Fine-tuning of Large Models with Extremely Low Communication Overhead of One Bit
  di: Cai, Zhijie, et al.
  Pubblicazione: (2025)