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Volumn , Issue , 2010, Pages

Humans learn using manifolds, reluctantly

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; LEARNING ALGORITHMS; LEARNING SYSTEMS;

EID: 85161973601     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (8)

References (11)
  • 1
    • 33750729556 scopus 로고    scopus 로고
    • Manifold regularization: A geometric framework for learning from labeled and unlabeled examples
    • November
    • Mikhail Belkin, Partha Niyogi, and Vikas Sindhwani. Manifold regularization: A geometric framework for learning from labeled and unlabeled examples. Journal of Machine Learning Research, 7:2399-2434, November 2006.
    • (2006) Journal of Machine Learning Research , vol.7 , pp. 2399-2434
    • Belkin, M.1    Niyogi, P.2    Sindhwani, V.3
  • 3
    • 0022686961 scopus 로고
    • Attention similarity, and the identification-categorization relationship
    • R. M. Nosofsky. Attention, similarity, and the identification- categorization relationship. Journal of Experimental Psychology: General, 115(1):39-57, 1986.
    • (1986) Journal of Experimental Psychology: General , vol.115 , Issue.1 , pp. 39-57
    • Nosofsky, R.M.1
  • 7
    • 64749109194 scopus 로고    scopus 로고
    • Semisupervised category learning: The impact of feedback in learning the information-integration task
    • Katleen Vandist, Maarten De Schryver, and Yves Rosseel. Semisupervised category learning: The impact of feedback in learning the information- integration task. Attention, Perception, & Psychophysics, 71(2):328-341, 2009.
    • (2009) Attention, Perception, & Psychophysics , vol.71 , Issue.2 , pp. 328-341
    • Vandist, K.1    De Schryver, M.2    Rosseel, Y.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.