Fed-Sparse-BNSL combines differential privacy with sparse greedy updates to learn linear Gaussian Bayesian network structures in a federated setting while keeping communication low and utility close to non-private baselines.
G Implementation and Computing Resources All experiments were conducted on CPUs, either on a personal computer or using a commodity cluster
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Differentially Private and Federated Structure Learning in Bayesian Networks
Fed-Sparse-BNSL combines differential privacy with sparse greedy updates to learn linear Gaussian Bayesian network structures in a federated setting while keeping communication low and utility close to non-private baselines.