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Mutually Reinforced Fair Multi-View Clustering
The proposed MR-FMVC optimizes fairness alignment and clustering iteratively to enable coordinated optimization and achieves a superior trade-off be-tween clustering performance and fairness.
FedIGL: Federated Invariant Graph Learning for Non-IID Graphs
This work proposes a FedIGL framework based on invariant learning, which effectively disrupts spurious correlations and further mines the invariant factors across different distributions, and proposes a novel Bi-Gradient Regularization strategy that introduces gradient constraints to guide the model in identifying clie...