Distributed Graph Estimation under Laplacian Constraints

•A distributed framework for estimating the graph Laplacian matrix with a known structure is formulated based on the maximization marginal likelihood (MML) approach.•An algorithm is developed to ensure estimation accuracy for low-dimensional local MML problems with singular target matrices in the distributed framework.•The proposed distributed method achieves the estimation accuracy of the centralized method while reducing the computational complexity significantly.