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Volumn 31, Issue 6, 2012, Pages

Active co-analysis of a set of shapes

Author keywords

Active learning; Semi supervised learning

Indexed keywords

ACTIVE LEARNING; ACTIVE LEARNING METHODS; CONSTRAINED CLUSTERING; FEATURE SPACE; SEMANTIC LABELING; SEMI-SUPERVISED LEARNING; SEMI-SUPERVISED LEARNING METHODS; SPARSE SET; SPRING SYSTEM;

EID: 84870234407     PISSN: 07300301     EISSN: 15577368     Source Type: Journal    
DOI: 10.1145/2366145.2366184     Document Type: Conference Paper
Times cited : (273)

References (36)
  • 5
    • 56449106588 scopus 로고    scopus 로고
    • Spectral clustering with inconsistent advice
    • COLEMAN, T., SAUNDERSON, J., AND WIRTH, A. 2008. Spectral clustering with inconsistent advice. In ICML, 152-159.
    • (2008) ICML , pp. 152-159
    • Coleman, T.1    Saunderson, J.2    Wirth, A.3
  • 8
    • 51949106897 scopus 로고    scopus 로고
    • Semi-supervised distance metric learning for collaborative image retrieval
    • HOI, S., LIU, W., AND CHANG, S. 2008. Semi-supervised distance metric learning for collaborative image retrieval. Proc. IEEE Conf. on CVPR.
    • (2008) Proc IEEE Conf. on CVPR
    • Hoi, S.1    Liu, W.2    Chang, S.3
  • 9
    • 84870188991 scopus 로고    scopus 로고
    • Co-segmentation of 3D shapes via subspace clustering
    • HU, R., FAN, L., AND LIU, L. 2012. Co-segmentation of 3D shapes via subspace clustering. Computer Graphics Forum (Proc. SGP) 31, 5, 1703-1713.
    • (2012) Computer Graphics Forum (Proc. SGP) , vol.31 , Issue.5 , pp. 1703-1713
    • H, U.R.1    Fan, L.2    Liu, L.3
  • 11
    • 84862019457 scopus 로고    scopus 로고
    • Unsupervised upright orientation of man-made models
    • JIN, Y., WU, Q., AND LIU, L. 2012. Unsupervised upright orientation of man-made models. Graphical Models 74, 4, 99-108.
    • (2012) Graphical Models , vol.74 , Issue.4 , pp. 99-108
    • Jin, Y.1    W, U.Q.2    Liu, L.3
  • 14
    • 9444294778 scopus 로고    scopus 로고
    • From instance-level constraints to space-level constraints: Making the most of prior knowledge in data clustering
    • KLEIN, D., KAMVAR, S., AND MANNING, C. 2002. From instance-level constraints to space-level constraints: Making the most of prior knowledge in data clustering. In ICML, 307-314.
    • (2002) ICML , pp. 307-314
    • Klein, D.1    Kamvar, S.2    Manning, C.3
  • 15
    • 31844447616 scopus 로고    scopus 로고
    • Semi-supervised graph clustering: A kernel approach
    • KULIS, B., BASU, S., DHILLON, I., AND MOONEY, R. 2005. Semi-supervised graph clustering: a kernel approach. In ICML, 457-464.
    • (2005) ICML , pp. 457-464
    • Kulis, B.1    Basu, S.2    Dhillon, I.3    Mooney, R.4
  • 16
    • 70450267700 scopus 로고    scopus 로고
    • Constrained clustering via spectral regularization
    • LI, Z., LIU, J., AND TANG, X. 2009. Constrained clustering via spectral regularization. In Proc. IEEE Conf. on CVPR, 421-428.
    • (2009) Proc IEEE Conf. on CVPR , pp. 421-428
    • L, I.Z.1    Liu, J.2    Tang, X.3
  • 17
    • 51949113919 scopus 로고    scopus 로고
    • Constrained spectral clustering through affinity propagation
    • LU, Z., AND CARREIRA-PERPINÁN, M. 2008. Constrained spectral clustering through affinity propagation. In Proc. IEEE Conf. on CVPR.
    • (2008) Proc IEEE Conf. on CVPR
    • L, U.Z.1    Carreira-Perpinán, M.2
  • 18
    • 68949137209 scopus 로고    scopus 로고
    • Active learning literature survey
    • Univ. of Wisconsin-Madison
    • SETTLES, B. 2009. Active learning literature survey. Tech. Rep. 1648, Univ. of Wisconsin-Madison.
    • (2009) Tech. Rep 1648
    • Settles, B.1
  • 19
    • 42949092365 scopus 로고    scopus 로고
    • A survey on mesh segmentation techniques
    • SHAMIR, A. 2008. A survey on mesh segmentation techniques. Computer Graphics Forum 27, 6, 1539-1556.
    • (2008) Computer Graphics Forum , vol.27 , Issue.6 , pp. 1539-1556
    • Shamir, A.1
  • 20
    • 41149100106 scopus 로고    scopus 로고
    • Consistent mesh partitioning and skeletonization using the shape diameter function
    • SHAPIRA, L., SHAMIR, A., AND COHEN-OR, D. 2008. Consistent mesh partitioning and skeletonization using the shape diameter function. The Visual Computer 24, 4, 249-259.
    • (2008) The Visual Computer , vol.24 , Issue.4 , pp. 249-259
    • Shapira, L.1    Shamir, A.2    Cohen-Or, D.3
  • 21
    • 84898968165 scopus 로고    scopus 로고
    • Computing Gaussian mixture models with em using equivalence constraints
    • SHENTAL, N., BAR-HILLEL, A., HERTZ, T., AND WEINSHALL, D. 2004. Computing Gaussian mixture models with EM using equivalence constraints. In Proc. NIPS, 465-472.
    • (2004) Proc. NIPS , pp. 465-472
    • Shental, N.1    Bar-Hillel, A.2    Hertz, T.3    Weinshall, D.4
  • 22
    • 0034244751 scopus 로고    scopus 로고
    • Normalized cuts and image segmentation
    • SHI, J., AND MALIK, J. 2000. Normalized cuts and image segmentation. IEEE PAMI 22, 8, 888-905.
    • (2000) IEEE PAMI , vol.22 , Issue.8 , pp. 888-905
    • Shi, J.1    Malik, J.2
  • 25
    • 84864062501 scopus 로고    scopus 로고
    • Large margin component analysis
    • TORRESANI, L., AND LEE, K. 2007. Large margin component analysis. In Proc. NIPS, vol. 19, 1385-1392.
    • (2007) Proc. NIPS , vol.19 , pp. 1385-1392
    • Torresani, L.1    Lee, K.2
  • 27
    • 0001898293 scopus 로고    scopus 로고
    • Clustering with instancelevel constraints
    • WAGSTAFF, K., AND CARDIE, C. 2000. Clustering with instancelevel constraints. In ICML, 1103-1110.
    • (2000) ICML , pp. 1103-1110
    • Wagstaff, K.1    Cardie, C.2
  • 28
    • 79951757648 scopus 로고    scopus 로고
    • Active spectral clustering
    • WANG, X., AND DAVIDSON, I. 2010. Active spectral clustering. In ICDM, IEEE, 561-568.
    • (2010) ICDM IEEE , pp. 561-568
    • Wang, X.1    Davidson, I.2
  • 29
    • 77956209057 scopus 로고    scopus 로고
    • Flexible constrained spectral clustering
    • WANG, X., AND DAVIDSON, I. 2010. Flexible constrained spectral clustering. In SIGKDD, 563-572.
    • (2010) SIGKDD , pp. 563-572
    • Wang, X.1    Davidson, I.2
  • 30
    • 33749257955 scopus 로고    scopus 로고
    • Distance metric learning for large margin nearest neighbor classification
    • WEINBERGER, K., BLITZER, J., AND SAUL, L. 2006. Distance metric learning for large margin nearest neighbor classification. In Proc. NIPS, vol. 18, 1473-1480.
    • (2006) Proc. NIPS , vol.18 , pp. 1473-1480
    • Weinberger, K.1    Blitzer, J.2    Saul, L.3
  • 31
    • 33745290657 scopus 로고    scopus 로고
    • Active constrained clustering by examining spectral eigenvectors
    • XU, Q., DESJARDINS, M., AND WAGSTAFF, K. 2005. Active constrained clustering by examining spectral eigenvectors. In Discovery Science, 294-307.
    • (2005) Discovery Science , pp. 294-307
    • X, U.Q.1    Desjardins, M.2    Wagstaff, K.3
  • 34
    • 35148876898 scopus 로고    scopus 로고
    • Distance metric learning: A comprehensive survey
    • Michigan State Universiy
    • YANG, L., AND JIN, R. 2006. Distance metric learning: A comprehensive survey. Tech. rep., Michigan State Universiy.
    • (2006) Tech. Rep.
    • Yang, L.1    Jin, R.2
  • 35
    • 0742321103 scopus 로고    scopus 로고
    • Segmentation given partial grouping constraints
    • YU, S., AND SHI, J. 2004. Segmentation given partial grouping constraints. IEEE PAMI 26, 2, 173-183.
    • (2004) IEEE PAMI , vol.26 , Issue.2 , pp. 173-183
    • Y, U.S.1    Shi, J.2
  • 36
    • 33745456231 scopus 로고    scopus 로고
    • Semi-supervised learning literature survey
    • Univ. of Wisconsin-Madison
    • ZHU, X. 2005. Semi-supervised learning literature survey. Tech. Rep. 1530, Univ. of Wisconsin-Madison.
    • (2005) Tech. Rep , vol.1530
    • Zhu, X.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.