12 citations · 25 across the 10 of their papers we have counts for
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cs.LG2024
Communication-Efficient Federated Learning with Adaptive Compression under Dynamic Bandwidth
Ying Zhuansun, Dandan Li, Xiaohong Huang +1
Federated learning can train models without directly providing local data to the server. However, the frequent updating of the local model brings the problem of large communication…
cs.GT2024
Maximizing NFT Incentives: References Make You Rich
Guangsheng Yu, Qin Wang, Caijun Sun +3
In this paper, we study how to optimize existing Non-Fungible Token (NFT) incentives. Upon exploring a large number of NFT-related standards and real-world projects, we come across…
cs.CR2024
TBDD: A New Trust-based, DRL-driven Framework for Blockchain Sharding in IoT
Zixu Zhang, Guangsheng Yu, Caijun Sun +7
Integrating sharded blockchain with IoT presents a solution for trust issues and optimized data flow. Sharding boosts blockchain scalability by dividing its nodes into parallel sha…