Comparison of two inference approaches in Gaussian graphical models

---

Copy For Citation

PURUTÇUOĞLU GAZİ V., AYYILDIZ DEMİRCİ E., Wit E.

TURKISH JOURNAL OF BIOCHEMISTRY-TURK BIYOKIMYA DERGISI, vol.42, no.2, pp.203-211, 2017 (SCI-Expanded)

• Publication Type: Article / Article
• Volume: 42 Issue: 2
• Publication Date: 2017
• Doi Number: 10.1515/tjb-2016-0298
• Journal Name: TURKISH JOURNAL OF BIOCHEMISTRY-TURK BIYOKIMYA DERGISI
• Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, TR DİZİN (ULAKBİM)
• Page Numbers: pp.203-211
• Middle East Technical University Affiliated: Yes

Abstract

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.