Title :
Latent Graph Inference and Validation
Author_Institution :
Dept. of Comput. Sci., Univ. of Illinois at Chicago, Chicago, IL, USA
Abstract :
Graphs are a fundamental model to describe complex statistical relationships over many scientific domains. In this context, graphs are commonly used to investigate relational phenomena which are not directly observable. Our work formulates a Latent Network Inference problem and develops inference methods in a common context for scientific applications where there is an absence of ground truth.
Keywords :
"Predictive models","Topology","Conferences","Data mining","Data models","Testing","Uncertainty"
Conference_Titel :
Data Mining Workshop (ICDMW), 2015 IEEE International Conference on
Electronic_ISBN :
2375-9259
DOI :
10.1109/ICDMW.2015.224