DNNLasso: Scalable Graph Learning for Matrix-Variate Data

1 code implementation • 5 Mar 2024 • Meixia Lin, Yangjing Zhang

We consider the problem of jointly learning row-wise and column-wise dependencies of matrix-variate observations, which are modelled separately by two precision matrices.

Graph Learning

Learning Graph Laplacian with MCP

no code implementations • 22 Oct 2020 • Yangjing Zhang, Kim-Chuan Toh, Defeng Sun

We consider the problem of learning a graph under the Laplacian constraint with a non-convex penalty: minimax concave penalty (MCP).