Research map / Federated learning and privacy / Personalized and heterogeneous FL

FedBN: Federated Learning on Non-IID Features via Local Batch Normalization

ICLR 2021 · Federated learning and privacy › Personalized and heterogeneous FL · approach: Federated learning with pretrained models · 342 citations (OpenAlex)

Read the paperCheck your idea against 108,967 papers

AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.

Closest papers by meaning

• FedWon: Triumphing Multi-domain Federated Learning Without Normalization (ICLR 2024 · similarity 0.90)
• Hybrid Batch Normalisation: Resolving the Dilemma of Batch Normalisation in Federated Learning (ICML 2025 · similarity 0.89)
• Population Normalization for Federated Learning (CVPR 2025 · similarity 0.88)
• Low Precision Local Training is Enough for Federated Learning (NeurIPS 2024 · similarity 0.87)
• FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data (ICLR 2024 · similarity 0.87)
• FedQS: Optimizing Gradient and Model Aggregation for Semi-Asynchronous Federated Learning (NeurIPS 2025 · similarity 0.87)