A low-rank buffer matrix that calibrates user embeddings and personalizes item embeddings reduces the distortion caused by federated aggregation and improves recommendation accuracy.
A survey on federated recommendation systems
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Beyond Personalization: Federated Recommendation with Calibration via Low-rank Decomposition
A low-rank buffer matrix that calibrates user embeddings and personalizes item embeddings reduces the distortion caused by federated aggregation and improves recommendation accuracy.