FedMChain improves multimodal federated learning by chaining modality-wise optimization phases with error-compensated regularization and sparse sign-guided aggregation to mitigate modality competition and cut communication overhead.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.DC 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Boosting Multimodal Federated Learning via Chained Modality Optimization
FedMChain improves multimodal federated learning by chaining modality-wise optimization phases with error-compensated regularization and sparse sign-guided aggregation to mitigate modality competition and cut communication overhead.