Analysis and Application of Matrix-Form Neural Networks for Fast Matrix-Variable Convex Optimization
Abstract: Matrix-variable optimization is a generalization of vector-variable optimization and has been found to have many important applications. To reduce computation time and storage requirement, ...
Abstract: In this paper, we propose two new algorithms for maximum-likelihood estimation (MLE) of high dimensional sparse covariance matrices. Unlike most of the state-of-the-art methods, which either ...
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