Prototype-Based Layered Federated Cross-Modal Hashing. (arXiv:2210.15678v1 [cs.LG])

Recently, deep cross-modal hashing has gained increasing attention. However,
in many practical cases, data are distributed and cannot be collected due to
privacy concerns, which greatly reduces the cross-modal hashing performance on
each client. And due to the problems of statistical heterogeneity, model
heterogeneity, and forcing each client to accept the same parameters, applying
federated learning to cross-modal hash learning becomes very tricky. In this
paper, we propose a novel method called prototype-based layered federated
cross-modal hashing. Specifically, the prototype …

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