3 papers
cs.LG2026
Federated Client Selection under Partial Visibility: A POMDP Approach with Spatio-Temporal Attention
Qijun Hou, Yuchen Shi, Pingyi Fan +1
Federated learning relies on effective client selection to alleviate the performance degradation caused by data heterogeneity. Most existing methods assume full visibility of all c…
cs.LG2026
FedGMI: Generative Model-Driven Federated Learning for Probabilistic Mixture Inference
Qijun Hou, Yuchen Shi, Pingyi Fan +1
Federated Learning (FL) facilitates collaborative model training across decentralized clients while preserving data privacy by avoiding raw data exchange. Despite its potential, FL…
cs.LG2026
EdgeFLow: Serverless Federated Learning via Sequential Model Migration in Edge Networks
Yuchen Shi, Qijun Hou, Pingyi Fan +1
Federated Learning (FL) has emerged as a transformative distributed learning paradigm in the era of Internet of Things (IoT), reconceptualizing data processing methodologies. Howev…