4 papers
A Unified Convergence Analysis for Semi-Decentralized Learning: Sampled-to-Sampled vs. Sampled-to-All Communication
Angelo Rodio, Giovanni Neglia, Zheng Chen +1
In semi-decentralized federated learning, devices primarily rely on device-to-device communication but occasionally interact with a central server. Periodically, a sampled subset o…
Distributed Average Consensus in Wireless Multi-Agent Systems with Over-the-Air Aggregation
Themistoklis Charalambous, Zheng Chen, Christoforos N. Hadjicostis
In this paper, we address the average consensus problem of multi-agent systems over wireless networks. We propose a distributed average consensus algorithm by invoking the concept…
Robust and Efficient Average Consensus with Non-Coherent Over-the-Air Aggregation
Yuhang Deng, Zheng Chen, Erik G. Larsson
Non-coherent over-the-air (OTA) computation has garnered increasing attention for its advantages in facilitating information aggregation among distributed agents in resource-constr…
Optimizing Privacy-Utility Trade-off in Decentralized Learning with Generalized Correlated Noise
Angelo Rodio, Zheng Chen, Erik G. Larsson
Decentralized learning enables distributed agents to collaboratively train a shared machine learning model without a central server, through local computation and peer-to-peer comm…