Bi-level multi-source learning for heterogeneous block-wise missing data

NeuroImage

Volumn 102, Issue P1, 2014, Pages 192-206

  Xiang, Shuo ^a,b   Yuan, Lei ^a,b   Fan, Wei ^c   Wang, Yalin ^a   Thompson, Paul M ^d   Ye, Jieping ^a,b  

^a ARIZONA STATE UNIVERSITY   (United States)

^b ARIZONA STATE UNIVERSITY   (United States)

^c HUAWEI NOAH S ARK LAB   (China)

^d UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Alzheimer's disease; Block wise missing data; Multi modal fusion; Multi source; Optimization

Indexed keywords

FLUORODEOXYGLUCOSE;

ALZHEIMER DISEASE; BILEVEL MULTISOURCE LEARNING; CEREBROSPINAL FLUID ANALYSIS; DATA ANALYSIS; GENE EXPRESSION; HUMAN; IMAGE ANALYSIS; IMAGE PROCESSING; IMAGING SOFTWARE; INFORMATION PROCESSING; LEARNING; LEARNING ALGORITHM; MATHEMATICAL ANALYSIS; NEUROIMAGING; NUCLEAR MAGNETIC RESONANCE IMAGING; POSITRON EMISSION TOMOGRAPHY; PREDICTION; PROTEIN EXPRESSION; PROTEOMICS; REVIEW; ALGORITHM; CEREBROSPINAL FLUID; DATA MINING; STATISTICS AND NUMERICAL DATA;

ALGORITHMS; ALZHEIMER DISEASE; DATA MINING; HUMANS; MAGNETIC RESONANCE IMAGING; NEUROIMAGING; POSITRON-EMISSION TOMOGRAPHY; PROTEOMICS;

EID: 84908378904     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2013.08.015     Document Type: Review

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