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Research questionHow can federated learning systems preprocess structured data consistently without sharing raw data or excessive communication?Federated participants may have missing values, inconsistent formats, and differently scaled features, even though training requires compatible transformations. Computing those transformations without pooling raw records creates privacy and communication constraints.
AI
Machine Learning
Statistical Machine Learning
Technology
Latest papersRecent research connected to this question, newest first.FedPS: Federated Preprocessing for structured data via aggregated StatisticsThe source describes FedPS, which uses local data sketches and aggregated statistics for federated preprocessing and extends Bayesian Linear Regression to horizontal and vertical settings. The supplied abstract claims flexible, communication-efficient, and consistent pipelines but does not provide detailed empirical results or specify additional privacy guarantees.research paper · Sep 3, 2026
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