DAGs with NO TEARS: Smooth Optimization for Structure Learning
arXiv: Machine Learning, Volume abs/1803.01422, 2018.
Estimating the structure of directed acyclic graphs (DAGs, also known as Bayesian networks) is a challenging problem since the search space of DAGs is combinatorial and scales superexponentially with the number of nodes. Existing approaches rely on various local heuristics for enforcing the acyclicity constraint and are not well-suited to...More
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