82 citations · 87 across the 6 of their papers we have counts for
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cs.LG2026
Federated Nested Learning: Collaborative Training of Self-Referential Memories for Test-Time Adaptation
Hong Chen, Pengcheng Wu, Yuanguo Lin +4
We rethink Federated Learning (FL) from a nested learning perspective, framing the core challenge as how to collaboratively learn optimization rules, not just static models, to tac…
cs.LG2025
Sharpness-aware Federated Graph Learning
Ruiyu Li, Peige Zhao, Guangxia Li +3
One of many impediments to applying graph neural networks (GNNs) to large-scale real-world graph data is the challenge of centralized training, which requires aggregating data from…
cs.LG2022★ 3 cited
Multi-scale Attention Flow for Probabilistic Time Series Forecasting
Shibo Feng, Chunyan Miao, Ke Xu +4
The probability prediction of multivariate time series is a notoriously challenging but practical task. On the one hand, the challenge is how to effectively capture the cross-serie…