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Comparison of two inference approaches in Gaussian graphical models

2017-04-01
Purutçuoğlu Gazi, Vilda
AYYILDIZ DEMİRCİ, EZGİ
Wit, Ernst
Introduction: The Gaussian Graphical Model (GGM) is one of the well-known probabilistic models which is based on the conditional independency of nodes in the biological system. Here, we compare the estimates of the GGM parameters by the graphical lasso (glasso) method and the threshold gradient descent (TGD) algorithm.