3 papers
cs.LG2026
Active Client Selection in Federated Trajectory Prediction with Uncertainty-Awareness and Heterogeneous Complexity
Yiming Xie, Muzi Peng, Fei Miao +2
Training sequence models such as transformers is now standard for autonomous vehicle trajectory prediction, yet assembling high-quality centralized datasets remains challenging bec…
cs.LG2026
Beyond Non-IID: Learner--Client Distribution Mismatch in Federated Learning
Yiming Xie, Lili Su, Ningfang Mi
Federated learning systems are increasingly deployed to facilitate collaborative model training across a heterogeneous client population. Existing practice mostly implicitly assume…
cs.LG2026
DART-FL: Burst-Aware Multitask Federated Learning under Dynamic Inference Demand at the Edge
Yiming Xie, Pinrui Yu, Geng Yuan +2
Edge intelligence systems increasingly require model training and online inference to coexist on resource-constrained devices, while inference demand can vary substantially across…