메뉴 건너뛰기




Volumn , Issue , 2013, Pages 825-832

Learning to rank using privileged information

Author keywords

Learning to rank; object classification; privileged information during training

Indexed keywords

CLASSIFICATION (OF INFORMATION);

EID: 84898813471     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2013.107     Document Type: Conference Paper
Times cited : (199)

References (28)
  • 2
    • 35148817020 scopus 로고    scopus 로고
    • Multi-modal clustering for multimedia collections
    • R. Bekkerman and J. Jeon. Multi-modal clustering for multimedia collections. In CVPR, 2007.
    • (2007) CVPR
    • Bekkerman, R.1    Jeon, J.2
  • 3
    • 51949086515 scopus 로고    scopus 로고
    • Correlational spectral clustering
    • M.B. Blaschko and C. H. Lampert. Correlational spectral clustering. In CVPR, 2008.
    • (2008) CVPR
    • Blaschko, M.B.1    Lampert, C.H.2
  • 4
    • 34247849152 scopus 로고    scopus 로고
    • Training a support vector machine in the primal
    • O. Chapelle. Training a support vector machine in the primal. Neural Computation, pages 1155-1178, 2007.
    • (2007) Neural Computation , pp. 1155-1178
    • Chapelle, O.1
  • 5
    • 80052418610 scopus 로고    scopus 로고
    • Multi-view learning in the presence of view disagreement
    • C. M. Christoudias, R. Urtasun, and T. Darrell. Multi-view learning in the presence of view disagreement. In UAI, 2008.
    • (2008) UAI
    • Christoudias, C.M.1    Urtasun, R.2    Darrell, T.3
  • 7
    • 84856671941 scopus 로고    scopus 로고
    • Annotator rationales for visual recognition
    • J. Donahue and K. Grauman. Annotator rationales for visual recognition. In ICCV, 2011.
    • (2011) ICCV
    • Donahue, J.1    Grauman, K.2
  • 10
    • 85067032737 scopus 로고    scopus 로고
    • On feature combination for multiclass object classification
    • P. Gehler and S. Nowozin. On feature combination for multiclass object classification. In ICCV, 2009.
    • (2009) ICCV
    • Gehler, P.1    Nowozin, S.2
  • 11
    • 0002714543 scopus 로고    scopus 로고
    • Making large-scale SVM learning practical
    • T. Joachims. Making large-scale SVM learning practical. In Advances in kernel methods, pages 169-184, 1999.
    • (1999) Advances in Kernel Methods , pp. 169-184
    • Joachims, T.1
  • 12
    • 0242456822 scopus 로고    scopus 로고
    • Optimizing search engines using clickthrough data
    • T. Joachims. Optimizing search engines using clickthrough data. In KDD, 2002.
    • (2002) KDD
    • Joachims, T.1
  • 14
    • 84925402963 scopus 로고    scopus 로고
    • Attribute-based classification for zero-shot visual object categorization
    • C. H. Lampert, H. Nickisch, and S. Harmeling. Attribute-based classification for zero-shot visual object categorization. PAMI, 2013.
    • (2013) PAMI
    • Lampert, C.H.1    Nickisch, H.2    Harmeling, S.3
  • 16
    • 0002288190 scopus 로고    scopus 로고
    • Multiple-instance learning for natural scene classification
    • O. Maron and A. L. Ratan. Multiple-instance learning for natural scene classification. In ICML, 1998.
    • (1998) ICML
    • Maron, O.1    Ratan, A.L.2
  • 17
    • 85162041112 scopus 로고    scopus 로고
    • On the theory of learning with privileged information
    • D. Pechyony and V. Vapnik. On the theory of learning with privileged information. In NIPS, 2010.
    • (2010) NIPS
    • Pechyony, D.1    Vapnik, V.2
  • 19
    • 79959771606 scopus 로고    scopus 로고
    • Improving fisher kernel for large-scale image classification
    • F. Perronnin, J. Śanchez, and T. Mensink. Improving fisher kernel for large-scale image classification. In ECCV, 2010.
    • (2010) ECCV
    • Perronnin, F.1    Śanchez, J.2    Mensink, T.3
  • 20
    • 80053439603 scopus 로고    scopus 로고
    • Learning multi-view neighborhood preserving projections
    • N. Quadrianto and C. H. Lampert. Learning multi-view neighborhood preserving projections. In ICML, 2011.
    • (2011) ICML
    • Quadrianto, N.1    Lampert, C.H.2
  • 22
    • 48849117633 scopus 로고    scopus 로고
    • Pegasos: Primal estimated sub-gradient solver for SVM
    • S. Shalev-Shwartz, Y. Singer, and N. Srebro. Pegasos: Primal estimated sub-gradient solver for SVM. In ICML, 2007.
    • (2007) ICML
    • Shalev-Shwartz, S.1    Singer, Y.2    Srebro, N.3
  • 23
    • 84859264808 scopus 로고    scopus 로고
    • Early versus late fusion in semantic video analysis
    • C. G. Snoek, M. Worring, and A. W. Smeulders. Early versus late fusion in semantic video analysis. In ACM MM, 2005.
    • (2005) ACM MM
    • Snoek, C.G.1    Worring, M.2    Smeulders, A.W.3
  • 25
    • 68149165759 scopus 로고    scopus 로고
    • A new learning paradigm: Learning using privileged information
    • V. Vapnik and A. Vashist. A new learning paradigm: Learning using privileged information. Neural Networks, 2009.
    • (2009) Neural Networks
    • Vapnik, V.1    Vashist, A.2
  • 27
    • 80052913382 scopus 로고    scopus 로고
    • A discriminative latent model of object classes and attributes
    • Y.Wang and G. Mori. A discriminative latent model of object classes and attributes. In ECCV, 2010.
    • (2010) ECCV
    • Wang, Y.1    Mori, G.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.