Graphical model estimation seeks to uncover the conditional independence structure among variables by estimating the graph of a probability distribution. In high-dimensional settings, where the number ...
This book offers a comprehensive framework for mastering the complexities of learning high-dimensional sparse graphical models through the use of conditional independence tests. These tests are ...
Statistical models based on Gaussian random variables occupy a central position in modern data analysis, offering a mathematically tractable framework for inference, prediction and dimensionality ...
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