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arXiv Statistics ML By Laura Montagnani, Anthony CC Coolen, Marianne A Jonker

An Accurate and Single-Communication Federated Inference Algorithm

Read the original on arXiv Statistics ML →

The paper introduces a federated inference algorithm that requires only a single communication round between participating centers and a coordinating server. By extending previous second‑order Taylor expansion methods to third‑order expansions, the algorithm more accurately approximates local log‑likelihood functions, especially when local sample sizes are small. Simulation studies based on real data show that this higher‑order approach improves inference accuracy while maintaining privacy, communication efficiency, and scalability for collaborative biomedical and epidemiological research.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Statistics ML.

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