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Volumn , Issue , 2014, Pages 2115-2122

Asymmetric sparse kernel approximations for large-scale visual search

Author keywords

high dimensional search; nearest neighbors; sparse kernel approximations

Indexed keywords

EMBEDDINGS;

EID: 84911420471     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2014.271     Document Type: Conference Paper
Times cited : (5)

References (24)
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    • A. Coates and A. Y. Ng. The importance of encoding versus training with sparse coding and vector quantization. In International Conference on Machine Learning (ICML), volume 8, page 10, 2011.
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    • Coates, A.1    Ng, A.Y.2
  • 8
    • 0031644241 scopus 로고    scopus 로고
    • Approximate nearest neighbors: Towards removing the curse of dimensionality
    • P. Indyk and R. Motwani. Approximate nearest neighbors: towards removing the curse of dimensionality. In ACM Symposium on Theory of Computing, pages 604-613, 1998.
    • (1998) ACM Symposium on Theory of Computing , pp. 604-613
    • Indyk, P.1    Motwani, R.2
  • 10
    • 0001654702 scopus 로고
    • Extensions of lipschitz mappings into a hilbert space
    • W. B. Johnson and J. Lindenstrauss. Extensions of Lipschitz mappings into a Hilbert space. Contemporary Mathematics, 26(1):189-206, 1984.
    • (1984) Contemporary Mathematics , vol.26 , Issue.1 , pp. 189-206
    • Johnson, W.B.1    Lindenstrauss, J.2
  • 12
    • 0037492265 scopus 로고    scopus 로고
    • Efficient search for approximate nearest neighbor in high dimensional spaces
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    • (2000) SIAM Journal on Computing , vol.30 , Issue.2 , pp. 457-474
    • Kushilevitz, E.1    Ostrovsky, R.2    Rabani, Y.3
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    • Modeling the shape of the scene: A holistic representation of the spatial envelope
    • A. Oliva and A. Torralba. Modeling the shape of the scene: A holistic representation of the spatial envelope. International Journal of Computer Vision, 42(3):145-175, 2001.
    • (2001) International Journal of Computer Vision , vol.42 , Issue.3 , pp. 145-175
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  • 20
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    • Nonlinear component analysis as a kernel eigenvalue problem
    • B. Schölkopf, A. Smola, and K.-R. Müller. Nonlinear component analysis as a kernel eigenvalue problem. Neural Computation, 10(5):1299-1319, 1998.
    • (1998) Neural Computation , vol.10 , Issue.5 , pp. 1299-1319
    • Schölkopf, B.1    Smola, A.2    Müller, K.-R.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.