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Jin-Cheng Cai

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Open access 2026

-FedVAE: Detached Posterior-Confidence Gating for Dimension-Wise KL Regularization in Personalized Federated Collaborative Filtering

: Federated Variational Autoencoders (VAEs) keep interaction data local, but existing federated VAE recommenders typically apply uniform KL regularization and do not adapt dimension-wise penalties to unreliable posteriors in sparse interaction scenarios. We propose α -FedVAE, which uses a detached, clipped normalized s...

Jin-Cheng Cai, Li-Jiao Feng, Ni Zhao · 0 citations
Open access 2026

StabFedVAE: Stabilizing Global-Local Latent Representations for Federated Recommendation

This work proposes StabFedVAE, a global-local variational autoencoder that disentangles shared and client-specific preference patterns and introduces a round-dependent local Kullback–Leibler (KL) penalty to stabilize the local posterior.

Jin-Cheng Cai, Li-Jiao Feng, Ni Zhao · 0 citations

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