2024
DOI: 10.1609/aaai.v38i13.29416
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CLIP-Guided Federated Learning on Heterogeneity and Long-Tailed Data

Jiangming Shi,
Shanshan Zheng,
Xiangbo Yin
et al.

Abstract: Federated learning (FL) provides a decentralized machine learning paradigm where a server collaborates with a group of clients to learn a global model without accessing the clients' data. User heterogeneity is a significant challenge for FL, which together with the class-distribution imbalance further enhances the difficulty of FL. Great progress has been made in large vision-language models, such as Contrastive Language-Image Pre-training (CLIP), which paves a new way for image classification and object recog… Show more

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Cited by 7 publications
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