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cs.LG2024
DNNLasso: Scalable Graph Learning for Matrix-Variate Data
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. Due to th…
cs.LG2020★ 2 cited
Learning Graph Laplacian with MCP
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). For solving the MCP penalized graphical model,…