Structured Graph Learning Via Laplacian Spectral Constraints

2 code implementations • NeurIPS 2019 • Sandeep Kumar, Jiaxi Ying, Jos'e Vin'icius de M. Cardoso, Daniel P. Palomar

Then we introduce a unified graph learning framework, lying at the integration of the spectral properties of the Laplacian matrix with Gaussian graphical modeling that is capable of learning structures of a large class of graph families.

Graph Learning