Encoding, ensemble and accelerating strategies for linear causal model discovery

This thesis made outstanding contribution in automating the discovery of linear causal models. It introduced a highly efficient discovery algorithm, which implements new encoding, ensemble and accelerating strategies. Theoretic research and experimental work showed that this new discovery algorithm outperforms the previous system in both accuracy and efficiency.