Symmetric bilinear regression for signal subgraph estimation
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发表刊物：
IEEE Transactions on Signal Processing
关键字：
Brain Connectomics, Coordinate Descent, Network Regression, Symmetric Bilinear Regression
摘要：
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.
备注：
arXiv:1804.09567.
合写作者：
Zhengwu Zhang, David B. Dunson
第一作者：
Lu Wang
卷号：
67
期号：
7
页面范围：
1929--1940
ISSN号：
1053-587X
是否译文：
否
学位：博士学位
职称：副教授
学科：统计学
所在单位：数学与统计学院