메뉴 건너뛰기




Volumn , Issue , 2010, Pages 579-588

Adaptive distances on sets of vectors

Author keywords

Adaptive distances; Complex objects; Distance learning; Graphs; Sets

Indexed keywords

ADAPTIVE DISTANCE; COMPLEX OBJECTS; DISTANCE LEARNING; GRAPHS; SETS;

EID: 79951732169     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2010.45     Document Type: Conference Paper
Times cited : (4)

References (34)
  • 1
    • 85141266799 scopus 로고    scopus 로고
    • Support vector machines for multiple-instance learning
    • Stuart Andrews, Ioannis Tsochantaridis, and Thomas Hofmann. Support vector machines for multiple-instance learning. In NIPS, 2002.
    • (2002) NIPS
    • Andrews, S.1    Tsochantaridis, I.2    Hofmann, T.3
  • 2
    • 42749094100 scopus 로고    scopus 로고
    • Learning probabilistic models of tree edit distance
    • August
    • M. Bernard, L. Boyer, A. Habrard, and M. Sebban. Learning probabilistic models of tree edit distance. Pattern Recognition, 41(8):2611-2629, August 2008.
    • (2008) Pattern Recognition , vol.41 , Issue.8 , pp. 2611-2629
    • Bernard, M.1    Boyer, L.2    Habrard, A.3    Sebban, M.4
  • 8
    • 0030649484 scopus 로고    scopus 로고
    • Solving the multiple instance problem with axis-parallel rectangles
    • PII S0004370296000343
    • Thomas G. Dietterich, Richard H. Lathrop, and Tomas Lozano-Perez. Solving the multiple instance problem with axis-parallel rectangles. Artificial Intelligence, 89(1-2):31-71, 1997. (Pubitemid 127412230)
    • (1997) Artificial Intelligence , vol.89 , Issue.1-2 , pp. 31-71
    • Dietterich, T.G.1    Lathrop, R.H.2    Lozano-Perez, T.3
  • 9
    • 84898941962 scopus 로고    scopus 로고
    • Adaptive nearest neighbor classification using support vector machines
    • MIT Press
    • Carlotta Domeniconi and Dimitrios Gunopulos. Adaptive nearest neighbor classification using support vector machines. In NIPS. MIT Press, 2002.
    • (2002) NIPS
    • Domeniconi, C.1    Gunopulos, D.2
  • 10
    • 0031338770 scopus 로고    scopus 로고
    • Distance measures for point sets and their computation
    • T Eiter and H. Mannila. Distance measures for point sets and their computation. Acta Informatica, 34(2):109-133, 1997. (Pubitemid 127359707)
    • (1997) Acta Informatica , vol.34 , Issue.2 , pp. 109-133
    • Eiter, T.1    Mannila, H.2
  • 11
    • 31844445614 scopus 로고    scopus 로고
    • Optimal assignment kernels for attributed molecular graphs
    • Holger Fröhich, Jörg Wegner, Florian Sieker, and Andreas Zell. Optimal assignment kernels for attributed molecular graphs. In ICML, 2005.
    • (2005) ICML
    • Fröhich, H.1    Wegner, J.2    Sieker, F.3    Zell, A.4
  • 12
    • 58049100940 scopus 로고    scopus 로고
    • Deterministic annealing for multiple-instance learning
    • P. V. Gehler and O. Chapelle. Deterministic annealing for multiple-instance learning. In AISTATS, 2007.
    • (2007) AISTATS
    • Gehler, P.V.1    Chapelle, O.2
  • 13
    • 84864030708 scopus 로고    scopus 로고
    • Metric learning by collapsing classes
    • MIT Press
    • Amir Globerson and Sam Roweis. Metric learning by collapsing classes. In NIPS 18. MIT Press, 2006.
    • (2006) NIPS 18
    • Globerson, A.1    Roweis, S.2
  • 15
    • 0035113097 scopus 로고    scopus 로고
    • The predictive toxicology challenge 2000-2001
    • C. Helma, R. D. King, S. Kramer, and A. Srinivasan. The predictive toxicology challenge 2000-2001. Bioinformatics, 17:107-108, 2001. (Pubitemid 32178021)
    • (2001) Bioinformatics , vol.17 , Issue.1 , pp. 107-108
    • Helma, C.1    King, R.D.2    Kramer, S.3    Srinivasan, A.4
  • 16
    • 14344265725 scopus 로고    scopus 로고
    • Boosting margin based distance functions for clustering
    • Tomer Hertz, Aharon Bar-Hillel, and Daphna Weinshall. Boosting margin based distance functions for clustering. In ICML, 2004.
    • (2004) ICML
    • Hertz, T.1    Aharon, B.-H.2    Weinshall, D.3
  • 17
    • 70450164149 scopus 로고    scopus 로고
    • Learning a distance metric from multi-instance multi-label data
    • R. Jin, S.J. Wang, and Z.H. Zhou. Learning a distance metric from multi-instance multi-label data. In CVPR, 2009.
    • (2009) CVPR
    • Jin, R.1    Wang, S.J.2    Zhou, Z.H.3
  • 18
    • 1942516950 scopus 로고    scopus 로고
    • Learning with idealized kernels
    • J.T. Kwok and I.W. Tsang. Learning with idealized kernels. In ICML, 2003.
    • (2003) ICML
    • Kwok, J.T.1    Tsang, I.W.2
  • 20
  • 21
    • 10044252062 scopus 로고    scopus 로고
    • A probabilistic approach to learning costs for graph edit distance
    • M. Neuhaus and H. Bunke. A probabilistic approach to learning costs for graph edit distance. In ICPR, pages III: 389-393, 2004.
    • (2004) ICPR , vol.3 , pp. 389-393
    • Neuhaus, M.1    Bunke, H.2
  • 22
    • 33744981648 scopus 로고    scopus 로고
    • Learning stochastic edit distance: Application in handwritten character recognition
    • DOI 10.1016/j.patcog.2006.03.011, PII S0031320306001245
    • Jose Oncina and Marc Sebban. Learning stochastic edit distance: Application in handwritten character recognition. Pattern Recognition, 39(9):1575 - 1587, 2006. (Pubitemid 43867574)
    • (2006) Pattern Recognition , vol.39 , Issue.9 , pp. 1575-1587
    • Oncina, J.1    Sebban, M.2
  • 24
    • 0035402326 scopus 로고    scopus 로고
    • A polynomial time computable metric between point sets
    • Jan Ramon and Maurice Bruynooghe. A polynomial time computable metric between point sets. Acta Informatica, 37(10):765-780, 2001. (Pubitemid 33384228)
    • (2001) Acta Informatica , vol.37 , Issue.10 , pp. 765-780
    • Ramon, J.1    Bruynooghe, M.2
  • 27
    • 33745963387 scopus 로고    scopus 로고
    • Kernel relevant component analysis for distance metric learning
    • Ivor W. Tsang, Pak-Ming Cheung, and James T. Kwok. Kernel relevant component analysis for distance metric learning. In IJCNN, 2005.
    • (2005) IJCNN
    • Tsang, I.W.1    Cheung, P.-M.2    Kwok, J.T.3
  • 29
    • 56449127513 scopus 로고    scopus 로고
    • Fast solvers and efficient implementations for distance metric learning
    • Kilian Q. Weinberger and Lawrence K. Saul. Fast solvers and efficient implementations for distance metric learning. In ICML, 2008.
    • (2008) ICML
    • Weinberger, K.Q.1    Saul, L.K.2
  • 31
    • 62949092105 scopus 로고    scopus 로고
    • Distances and (indefinite) kernels for sets of objects
    • Hong Kong
    • Adam Woźnica, Alexandros Kalousis, and Melanie Hilario. Distances and (indefinite) kernels for sets of objects. In ICDM, Hong Kong, 2006.
    • (2006) ICDM
    • Woźnica, A.1    Kalousis, A.2    Hilario, M.3
  • 32
    • 79951756948 scopus 로고    scopus 로고
    • Learning to combine distances for complex representations
    • Adam Woźnica, Alexandros Kalousis, and Melanie Hilario. Learning to combine distances for complex representations. In ICML, 2007.
    • (2007) ICML
    • Woźnica, A.1    Kalousis, A.2    Hilario, M.3
  • 33
    • 79951747623 scopus 로고    scopus 로고
    • Adaptive matching based kernels for labeled graphs
    • Adam Woźnica, Alexandros Kalousis, and Melanie Hilario. Adaptive matching based kernels for labeled graphs. In PAKDD, 2010.
    • (2010) PAKDD
    • Woźnica, A.1    Kalousis, A.2    Hilario, M.3
  • 34
    • 84879571292 scopus 로고    scopus 로고
    • Distance metric learning with application to clustering with side-information
    • MIT Press
    • Eric P. Xing, Andrew Y. Ng, Michael I. Jordan, and Stuart Russell. Distance metric learning with application to clustering with side-information. In NIPS. MIT Press, 2003.
    • (2003) NIPS
    • Xing, E.P.1    Ng, A.Y.2    Jordan, M.I.3    Russell, S.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.