6 citations · 12 across the 7 of their papers we have counts for
4 papers · 1 filter
Boost Decentralized Federated Learning in Vehicular Networks by Diversifying Data Sources
Dongyuan Su, Yipeng Zhou, Laizhong Cui
Recently, federated learning (FL) has received intensive research because of its ability in preserving data privacy for scattered clients to collaboratively train machine learning…
A Fast Blockchain-based Federated Learning Framework with Compressed Communications
Laizhong Cui, Xiaoxin Su, Yipeng Zhou
Recently, blockchain-based federated learning (BFL) has attracted intensive research attention due to that the training process is auditable and the architecture is serverless avoi…
Optimal Rate Adaption in Federated Learning with Compressed Communications
Laizhong Cui, Xiaoxin Su, Yipeng Zhou +1
Federated Learning (FL) incurs high communication overhead, which can be greatly alleviated by compression for model updates. Yet the tradeoff between compression and model accurac…
Slashing Communication Traffic in Federated Learning by Transmitting Clustered Model Updates
Laizhong Cui, Xiaoxin Su, Yipeng Zhou +1
Federated Learning (FL) is an emerging decentralized learning framework through which multiple clients can collaboratively train a learning model. However, a major obstacle that im…