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Volumn , Issue , 2011, Pages 1541-1546

Heterogeneous domain adaptation using manifold alignment

Author keywords

[No Author keywords available]

Indexed keywords

COMMON FEATURES; CORRESPONDENCE RELATIONSHIPS; EXISTING DOMAINS; HETEROGENEOUS DOMAINS; MANIFOLD ALIGNMENTS; MULTIPLE SOURCE; NEW APPROACHES; PRE-PROCESSING STEP;

EID: 84863261451     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.5591/978-1-57735-516-8/IJCAI11-259     Document Type: Conference Paper
Times cited : (441)

References (12)
  • 2
    • 33750729556 scopus 로고    scopus 로고
    • Manifold regularization: A geometric framework for learning from labeled and unlabeled examples
    • Belkin, M.; Niyogi, P.; and Sindhwani, V. 2006. Manifold regularization: a geometric framework for learning from labeled and unlabeled examples. Journal of Machine Learning Research 2399-2434. (Pubitemid 44708005)
    • (2006) Journal of Machine Learning Research , vol.7 , pp. 2399-2434
    • Belkin, M.1    Niyogi, P.2    Sindhwani, V.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.