Bayesian Multilevel-multiclass Graphical Model
Gaussian graphical model has been a popular tool to investigate conditional dependency between random variables by estimating sparse precision matrices. Two problems have been discussed. One is to learn multiple Gaussian graphical models at multilevel from unknown classes. Another one is to select G...
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Virginia Tech
2020
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| Online Access: | http://hdl.handle.net/10919/101092 |