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cs.LG2026
Mosaic: Data-Free Knowledge Distillation via Mixture-of-Experts for Heterogeneous Distributed Environments
Junming Liu, Yanting Gao, Yuqi Li +6
Federated Learning (FL) is a decentralized machine learning paradigm that enables clients to collaboratively train models while preserving data privacy. However, the coexistence of…
cs.LG2025
TimeMKG: Knowledge-Infused Causal Reasoning for Multivariate Time Series Modeling
Yifei Sun, Junming Liu, Yirong Chen +2
Multivariate time series data typically comprises two distinct modalities: variable semantics and sampled numerical observations. Traditional time series models treat variables as…
cs.LG2025
FedRecon: Missing Modality Reconstruction in Heterogeneous Distributed Environments
Junming Liu, Yanting Gao, Yifei Sun +4
Multimodal data are often incomplete and exhibit Non-Independent and Identically Distributed (Non-IID) characteristics in real-world scenarios. These inherent limitations lead to b…