Author

Ning-Fang Mi

h-index 2 View on Semantic Scholar

We have 3 of 10 papers

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

#machine learning Preprint Aug 2026

Active Client Selection in Federated Trajectory Prediction with Uncertainty-Awareness and Heterogeneous Complexity

Training sequence models such as transformers is now standard for autonomous vehicle trajectory prediction, yet assembling high-quality centralized datasets remains challenging because real-world trajectories are fragmented across regions and vehicles. Federated Learning (FL) offers a natural alternative, but faces two...

Yi-Ming Xie, Mu-Zi Peng, Fei Miao et al. · 0 citations

#machine learning Preprint Aug 2026

Beyond Non-IID: Learner--Client Distribution Mismatch in Federated Learning

This paper considers the practical setting where the learner keeps a small proxy dataset, and proposes a dynamic, influence-aware client selection framework that estimates each client's potential utility to the learner's optimization objective using proxy influence signals on a learner-specific proxy set.

Yi-Ming Xie, Linghui Su, Ning-Fang Mi · 0 citations

#machine learning Preprint Aug 2026

DART-FL: Burst-Aware Multitask Federated Learning under Dynamic Inference Demand at the Edge

Results show that DART-FL dynamically adapts the inference-training resource split to time-varying inference demand and shifts the learning progress of high-demand tasks toward their burst periods, improving model accuracy when those tasks are frequently requested while maintaining comparable long-term multitask perfor...

Yi-Ming Xie, Pinrui Yu, Geng Yuan et al. · 0 citations