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Communication-Efficient Split Learning Based on Analog Communication and Over the Air Aggregation
Split-learning (SL) has recently gained popularity due to its inherent privacy-preserving capabilities and ability to enable collaborative inference for devices with limited computational power.
Energy-Efficient Model Compression and Splitting for Collaborative Inference Over Time-Varying Channels
In this paper, we propose a technique to reduce the total energy bill at the edge device by utilizing model compression and time-varying model split between the edge and remote nodes.
Cross Layer Optimization and Distributed Reinforcement Learning Approach for Tile-Based 360 Degree Wireless Video Streaming
Wirelessly streaming high quality 360 degree videos is still a challenging problem.
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