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Volumn 1, Issue , 2010, Pages 587-592

Multi-instance dimensionality reduction

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING ALGORITHMS;

EID: 77958555954     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (15)

References (18)
  • 1
    • 84898946229 scopus 로고    scopus 로고
    • Support vector machines for multiple-instance learning
    • Andrews, S.; Tsochantaridis, I.; and Hofmann, T. 2003. Support vector machines for multiple-instance learning. In NIPS 15. 561-568.
    • (2003) NIPS , vol.15 , pp. 561-568
    • Andrews, S.1    Tsochantaridis, I.2    Hofmann, T.3
  • 3
  • 5
    • 77958520605 scopus 로고    scopus 로고
    • A review of multi-instance learning assumptions
    • in press
    • Foulds, J., and Frank, E. 2009. A review of multi-instance learning assumptions. Knowledge Engineering Review, in press.
    • (2009) Knowledge Engineering Review
    • Foulds, J.1    Frank, E.2
  • 7
    • 84864047275 scopus 로고    scopus 로고
    • Multiple instance learning for computer aided diagnosis
    • Fung, G.; Dundar, M; Krishnappuram, B.; and Rao, R. B. 2007. Multiple instance learning for computer aided diagnosis. In NIPS 19. 425-432.
    • (2007) NIPS , vol.19 , pp. 425-432
    • Fung, G.1    Dundar, M.2    Krishnappuram, B.3    Rao, R.B.4
  • 10
    • 70349967917 scopus 로고    scopus 로고
    • A convex method for locating regions of interest with multi-instance learning
    • Li, Y.-F; Kwok, J. T; Tsang, I. W.; and Zhou, Z.-H. 2009. A convex method for locating regions of interest with multi-instance learning. In ECML PKDD, 15-3O.
    • (2009) ECML PKDD , pp. 15-30
    • Li, Y.-F.1    Kwok, J.T.2    Tsang, I.W.3    Zhou, Z.-H.4
  • 12
    • 0034387718 scopus 로고    scopus 로고
    • Improving the convergence of non-interior point algorithms for nonlinear complementarity problems
    • Qi, L., and Sun, D. 2000. Improving the convergence of non-interior point algorithms for nonlinear complementarity problems. Mathematics of Computation 69:283-304.
    • (2000) Mathematics of Computation , vol.69 , pp. 283-304
    • Qi, L.1    Sun, D.2
  • 13
    • 31844448950 scopus 로고    scopus 로고
    • Supervised versus multiple instance learning: An empirical comparison
    • Ray, S., and Craven, M. 2005. Supervised versus multiple instance learning: An empirical comparison. In ICML, 697-704.
    • (2005) ICML , pp. 697-704
    • Ray, S.1    Craven, M.2
  • 14
    • 56449092895 scopus 로고    scopus 로고
    • Bayesian multiple instance learning: Automatic feature selection and inductive transfer
    • Raykar, V. C; Krishnapuram, B.; Bi, J.; Dundar, M.; and Rao, R. B. 2008. Bayesian multiple instance learning: Automatic feature selection and inductive transfer. In ICML, 808-815.
    • (2008) ICML , pp. 808-815
    • Raykar, V.C.1    Krishnapuram, B.2    Bi, J.3    Dundar, M.4    Rao, R.B.5
  • 15
    • 0000545783 scopus 로고
    • Richtungsfelder und fernparallelismus in n-dimensionalel manning faltigkeiten
    • Stiefel, E. 1935. Richtungsfelder und fernparallelismus in n-dimensionalel manning faltigkeiten. Comentarii Mathematici Helvetia 8:305-353.
    • (1935) Comentarii Mathematici Helvetia , vol.8 , pp. 305-353
    • Stiefel, E.1
  • 16
    • 45549083257 scopus 로고    scopus 로고
    • Multiple instance boosting for object detection
    • Viola, P.; Piatt, J.; and Zhang, C. 2006. Multiple instance boosting for object detection. In NIPS 18. 1419-1426.
    • (2006) NIPS , vol.18 , pp. 1419-1426
    • Viola, P.1    Piatt, J.2    Zhang, C.3
  • 17
    • 7444219637 scopus 로고    scopus 로고
    • Logistic regression and boosting for labeled bags of instances
    • Xin, X., and Frank, E. 2004. Logistic regression and boosting for labeled bags of instances. In PAKDD, 272-281.
    • (2004) PAKDD , pp. 272-281
    • Xin, X.1    Frank, E.2
  • 18
    • 33745613010 scopus 로고    scopus 로고
    • Locating regions of interest in CBIR with multi-instance learning techniques
    • Zhou, Z.-H.; Xue, X.-B.; and Jiang, Y. 2005. Locating regions of interest in CBIR with multi-instance learning techniques. In AJCAI, 92-101.
    • (2005) AJCAI , pp. 92-101
    • Zhou, Z.-H.1    Xue, X.-B.2    Jiang, Y.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.