Exact Recovery in Community Detection with Continuous-Valued Side Information
Date
2019-02
Authors
ORCID
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE-inst Electrical Electronics Engineers Inc
item.page.doi
Abstract
The community detection problem, as a special case of inference on graphs, has received much attention lately. However, in the presence of continuous-valued side information, the behavior of a sharp threshold for exact recovery has remained open, and is addressed in this letter. The new proof presented herein has the further advantage of closing the gap between necessary and sufficient conditions for exact recovery threshold that has existed in community detection under finite-alphabet side information.
Description
Due to copyright restrictions and/or publisher's policy full text access from Treasures at UT Dallas is limited to current UTD affiliates (use the provided Link to Article).
Keywords
Engineering, Graph theory, Random variables, Signal processing, Social networks, Stochastic processes
item.page.sponsorship
Rights
©2018 IEEE