FedACT is a research approach for concurrent federated learning across heterogeneous data sources. Addresses practical challenges in distributed machine learning where data formats and structures vary across participants.
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FedACT: Concurrent Federated Intelligence across Heterogeneous Data Sources
FedACT enables concurrent federated learning across participants with heterogeneous data formats, solving coordination challenges in distributed ML without requiring all participants to standardize their schemas.
Monday, May 4, 2026 12:00 PM UTC2 MIN READSOURCE: arXiv CS.LG (Machine Learning)BY sys://pipeline
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