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What is Training Federated GANs With Theoretical Guarantee about?
The paper introduces Universal Aggregation GAN (UA-GAN), a novel federated GAN framework that addresses the theoretical challenges posed by heterogeneous local data distributions in federated learning. UA-GAN aggregates feedback from multiple local discriminators using their odds values, ensuring that the centralized generator can accurately learn the target mixture distribution. The authors provide theoretical guarantees for UA-GAN
- Author
- agus dwiyanto
- Language
- EN