Symmetric bilinear regression for signal subgraph estimation

Release time:2018-09-07

Journal:IEEE Transactions on Signal Processing

Key Words:Brain Connectomics, Coordinate Descent, Network Regression, Symmetric Bilinear Regression

Abstract:There is increasing interest in learning a set of small outcome-relevant subgraphs in network-predictor regression. The extracted signal subgraphs can greatly improve the interpretation of the association between the network predictor and the response. In brain connectomics, the brain network for an individual corresponds to a set of interconnections among brain regions and there is a strong interest in linking the brain connectome to human cognitive traits. Modern neuroimaging technology allows a very fine segmentation of the brain, producing very large structural brain networks.

Note:arXiv:1804.09567.

Co-author:Zhengwu Zhang, David B. Dunson

First Author:Lu Wang

Volume:67

Issue:7

Page Number:1929--1940

ISSN No.:1053-587X

Translation or Not:no

Date of Publication:2019-04-01