• Corpus ID: 235421892

DAGs with No Curl: An Efficient DAG Structure Learning Approach

@article{Yu2021DAGsWN,
  title={DAGs with No Curl: An Efficient DAG Structure Learning Approach},
  author={Yue Yu and Tian Gao and Naiyu Yin and Qiang Ji},
  journal={ArXiv},
  year={2021},
  volume={abs/2106.07197}
}
Recently directed acyclic graph (DAG) structure learning is formulated as a constrained continuous optimization problem with continuous acyclicity constraints and was solved iteratively through subproblem optimization. To further improve efficiency, we propose a novel learning framework to model and learn the weighted adjacency matrices in the DAG space directly. Specifically, we first show that the set of weighted adjacency matrices of DAGs are equivalent to the set of weighted gradients of… 
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