Federated Adaptive Prompt Tuning for Multi-Domain Collaborative Learning

arXiv:2211.07864v4 Announce Type: replace
Abstract: Federated learning (FL) enables multiple clients to collaboratively train a global model without disclosing their data. Previous researches often require training the complete model parameters. However, the emergence of powerful pre-trained models makes it possible to achieve higher performance with fewer learnable parameters in FL. In this paper, we propose a federated adaptive prompt tuning algorithm, FedAPT, for multi-domain collaborative image classification with powerful foundation models, like CLIP. Compared with direct federated prompt tuning, our …

arxiv collaborative cs.cv cs.lg domain prompt prompt tuning type