Regret-Based Federated Causal Discovery with Unknown Interventions

This research explores a novel method for causal discovery in federated learning settings, especially when interventions are unknown. It focuses on how to identify causal relationships across distributed datasets without centralizing data, which has significant implications for privacy-preserving AI and robust decision-making in complex systems.