Multi-source learning with block-wise missing data for Alzheimer's disease prediction

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn Part F128815, Issue , 2013, Pages 185-193

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

^a Computer Science and Engineering ^*  (United States)

^b ARIZONA STATE UNIVERSITY   (United States)

^c HUAWEI NOAH S ARK LAB   (China)

^d Laboratory of Neuro Imaging   (United States)

Author keywords

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

Indexed keywords

DATA MINING; DIAGNOSIS; NEURODEGENERATIVE DISEASES; OPTIMIZATION;

ALZHEIMER'S DISEASE; COMPREHENSIVE EVALUATION; HETEROGENEOUS SOURCES; MISSING DATA; MULTI-SOURCES; MULTIPLE DATA SOURCES; OPTIMIZATION ALGORITHMS; TRADITIONAL TECHNIQUES;

EDUCATION;

EID: 84991665233     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2487575.2487594     Document Type: Conference Paper

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