DeFed-GMM-DaDiL enables stable decentralized domain adaptation by approximating client GMMs through shared learnable atoms and labeled Wasserstein barycenters, reconstructing missing classes competitively.
Wasserstein Distance Guided Representation Learning for Domain Adaptation , volume =
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DeFed-GMM-DaDiL: A Decentralized Federated Framework for Domain Adaptation
DeFed-GMM-DaDiL enables stable decentralized domain adaptation by approximating client GMMs through shared learnable atoms and labeled Wasserstein barycenters, reconstructing missing classes competitively.