AINeutralarXiv – CS AI · 18h ago6/10
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Causal Unlearning in Collaborative Optimization: Exact and Approximate Influence Reversal under Adversarial Contributions
Researchers present HF-KCU, a federated learning method that efficiently removes clients' data contributions while maintaining privacy compliance, achieving 47.75x speedup over retraining while preserving model accuracy. The technique uses Krylov subspace approximations and causal weighting to handle data deletion requests in production systems without compromising unaffected participants.