Regret-Based Federated Causal Discovery with Unknown Interventions 事件

Regret-Based Federated Causal Discovery with Unknown Interventions arXiv:2512.23626v2 Announce Type: replace Abstract: Most causal discovery methods recover a completed partially directed acyclic graph representing a Markov equivalence class from observational data. Recent work has extended these methods to federated settings to address data decentralization and privacy constraints, but often under idealized assumptions that all clients share the same causal model. Such assumptions are unrealis