Cross-domain learning from multiple sources: A consensus regularization perspective

IEEE Transactions on Knowledge and Data Engineering

Volumn 22, Issue 12, 2010, Pages 1664-1678

  Zhuang, Fuzhen ^a,b   Luo, Ping ^c   Xiong, Hui ^d   Xiong, Yuhong ^c   He, Qing ^a   Shi, Zhongzhi ^a  

^a INSTITUTE OF COMPUTING TECHNOLOGY   (China)

^b UNIVERSITY OF CHINESE ACADEMY OF SCIENCES   (China)

^c HEWLETT PACKARD LABORATORIES   (United States)

^d RUTGERS UNIVERSITY   (United States)

Author keywords

Classification; consensus regularization; cross domain learning; multiple source domains

Indexed keywords

CLASSIFICATION; CONSENSUS REGULARIZATION; CROSS-DOMAIN; DATA CHARACTERISTICS; DATA DISTRIBUTION; DIFFERENT DOMAINS; EMPIRICAL STUDIES; LEARNING METHODS; LEARNING MODELS; LEARNING PERFORMANCE; LOCAL CLASSIFIER; LOCAL DATA; MULTIPLE SOURCE; PRIVACY CONCERNS; REGULARIZATION FRAMEWORK; SINGLE SOURCE; TARGET DOMAIN; TEXT CATEGORIZATION;

CLASSIFIERS;

TEXT PROCESSING;

EID: 78149253779     PISSN: 10414347     EISSN: None     Source Type: Journal    
DOI: 10.1109/TKDE.2009.205     Document Type: Review

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