HF-KCU approximates influence reversal in federated learning using Krylov subspace conjugate gradients and causal weighting to achieve efficient unlearning with bounded adversarial robustness.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , pages =
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Causal Unlearning in Collaborative Optimization: Exact and Approximate Influence Reversal under Adversarial Contributions
HF-KCU approximates influence reversal in federated learning using Krylov subspace conjugate gradients and causal weighting to achieve efficient unlearning with bounded adversarial robustness.