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Volumn 1, Issue , 2012, Pages 287-295

Multi-task vector field learning

Author keywords

[No Author keywords available]

Indexed keywords

DIFFERENTIAL STRUCTURE; DIRECTIONAL DERIVATIVE; GENERALIZATION PERFORMANCE; GEOMETRIC STRUCTURE; LOW-DIMENSIONAL SUBSPACE; MULTITASK LEARNING; REGULARIZATION FRAMEWORK; SYNTHETIC AND REAL DATA;

EID: 84877772304     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (7)

References (20)
  • 2
    • 27844439373 scopus 로고    scopus 로고
    • A framework for learning predictive structures from multiple tasks and unlabeled data
    • R. K. Ando and T. Zhang. A framework for learning predictive structures from multiple tasks and unlabeled data. Journal of Machine Learning Research, 6:1817-1853, 2005.
    • (2005) Journal of Machine Learning Research , vol.6 , pp. 1817-1853
    • Ando, R.K.1    Zhang, T.2
  • 4
    • 0346238931 scopus 로고    scopus 로고
    • Task clustering and gating for Bayesian multitask learning
    • B. Bakker and T. Heskes. Task clustering and gating for bayesian multitask learning. Journal of Machine Learning Research, 4:83-99, 2003.
    • (2003) Journal of Machine Learning Research , vol.4 , pp. 83-99
    • Bakker, B.1    Heskes, T.2
  • 5
    • 33750729556 scopus 로고    scopus 로고
    • Manifold regularization: A geometric framework for learning from labeled and unlabeled examples
    • December
    • M. Belkin, P. Niyogi, and V. Sindhwani. Manifold regularization: A geometric framework for learning from labeled and unlabeled examples. Journal of Machine Learning Research, 7:2399-2434, December 2006.
    • (2006) Journal of Machine Learning Research , vol.7 , pp. 2399-2434
    • Belkin, M.1    Niyogi, P.2    Sindhwani, V.3
  • 7
    • 9444270330 scopus 로고    scopus 로고
    • Exploiting task relatedness for mulitple task learning
    • S. Ben-David and R. Schuller. Exploiting task relatedness for mulitple task learning. In Conference on Learning Theory, pages 567-580, 2003.
    • (2003) Conference on Learning Theory , pp. 567-580
    • Ben-David, S.1    Schuller, R.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.