4 papers · 1 filter
Fedcompass: Federated Clustered and Periodic Aggregation Framework for Hybrid Classical-Quantum Models
Yueheng Wang, Xing He, Zinuo Cai +4
Federated learning enables collaborative model training across decentralized clients under privacy constraints. Quantum computing offers potential for alleviating computational and…
Federated learning over physical channels: adaptive algorithms with near-optimal guarantees
Rui Zhang, Wenlong Mou
In federated learning, communication cost can be significantly reduced by transmitting the information over the air through physical channels. In this paper, we propose a new class…
GDBR: Label Recovery Attack Against Partial Gradient Encryption in Federated Learning
Rui Zhang, Ka-Ho Chow
The increasing demand for data privacy, alongside the benefits of aggregating data from networked devices, has catalyzed the emergence of federated learning (FL). In FL, clients jo…
Geminio: Language-Guided Gradient Inversion Attacks in Federated Learning
Junjie Shan, Ziqi Zhao, Jialin Lu +3
Foundation models that bridge vision and language have made significant progress. While they have inspired many life-enriching applications, their potential for abuse in creating n…