메뉴 건너뛰기




Volumn 22, Issue 1, 2010, Pages 76-89

MILD: Multiple-instance learning via disambiguation

Author keywords

CBIR; Co training; Drug activity prediction.; Learning from ambiguity; Multiple instance learning; Object recognition

Indexed keywords

CLASS LABELS; CLASSIFICATION ,; CO-TRAINING; DISAMBIGUATION METHOD; FEATURE REPRESENTATION; MULTIPLE INSTANCES; MULTIPLE-INSTANCE LEARNING; SEMI-SUPERVISED LEARNING METHODS; TRAINING SETS; TRUE POSITIVE;

EID: 72949121319     PISSN: 10414347     EISSN: None     Source Type: Journal    
DOI: 10.1109/TKDE.2009.58     Document Type: Article
Times cited : (75)

References (40)
  • 1
    • 0030649484 scopus 로고    scopus 로고
    • Solving the multiple instance problem with axis-parallel rectangles
    • T.G. Dietterich, R.H. Lathrop, and T. Lozano-Pérez, "Solving the Multiple Instance Problem with Axis-Parallel Rectangles," Artificial Intelligence, vol.89, nos. 1/2, pp. 31-71, 1997.
    • (1997) Artificial Intelligence , vol.89 , Issue.1-2 , pp. 31-71
    • Dietterich, T.G.1    Lathrop, R.H.2    Lozano-Pérez, T.3
  • 2
    • 31844448950 scopus 로고    scopus 로고
    • Supervised versus multiple instance learning: An empirical comparison
    • S. Ray and M. Craven, "Supervised versus Multiple Instance Learning: An Empirical Comparison," Proc. Int'l Conf. Machine Learning, 2005.
    • (2005) Proc. Int'l Conf. Machine Learning
    • Ray, S.1    Craven, M.2
  • 4
    • 84863161940 scopus 로고    scopus 로고
    • Image categorization by learning and reasoning with regions
    • Y. Chen and J.Z. Wang, "Image Categorization by Learning and Reasoning with Regions," J. Machine Learning Research, vol.5, pp. 913-939, 2004.
    • (2004) J. Machine Learning Research , vol.5 , pp. 913-939
    • Chen, Y.1    Wang, J.Z.2
  • 9
    • 34547984757 scopus 로고    scopus 로고
    • On the relation between multi-instance learning and semi-supervised learning
    • Z.-H. Zhou and J.-M. Xu, "On the Relation between Multi-Instance Learning and Semi-Supervised Learning," Proc. Int'l Conf. Machine Learning, 2007.
    • (2007) Proc. Int'l Conf. Machine Learning
    • Zhou, Z.-H.1    Xu, J.-M.2
  • 11
    • 33947180489 scopus 로고    scopus 로고
    • MILES: Multiple-instance learning via embedded instance selection
    • Dec.
    • Y. Chen, J. Bi, and J.Z. Wang, "MILES: Multiple-Instance Learning via Embedded Instance Selection," IEEE Trans. Pattern Analysis and Machine Intelligence, vol.28, no.12, pp. 1931-1947, Dec. 2006.
    • (2006) IEEE Trans. Pattern Analysis and Machine Intelligence , vol.28 , Issue.12 , pp. 1931-1947
    • Chen, Y.1    Bi, J.2    Wang, J.Z.3
  • 12
    • 0031620208 scopus 로고    scopus 로고
    • Combining labeled and unlabeled data with Co-Training
    • A. Blum and T.M. Mitchell, "Combining Labeled and Unlabeled Data with Co-Training," Proc. Ann. Conf. Learning Theory, pp. 92-100, 1998.
    • (1998) Proc. Ann. Conf. Learning Theory , pp. 92-100
    • Blum, A.1    Mitchell, T.M.2
  • 13
    • 34547973746 scopus 로고    scopus 로고
    • An integrated approach to feature invention and model construction for drug activity prediction
    • J. Davis, V.S. Costa, S. Ray, and D. Page, "An Integrated Approach to Feature Invention and Model Construction for Drug Activity Prediction," Proc. Int'l Conf. Machine Learning, 2007.
    • (2007) Proc. Int'l Conf. Machine Learning
    • Davis, J.1    Costa, V.S.2    Ray, S.3    Page, D.4
  • 14
    • 0002469253 scopus 로고    scopus 로고
    • On learning from multi-instance examples: Empirical evaluation of a theoretical approach
    • P. Auer, "On Learning from Multi-Instance Examples: Empirical Evaluation of a Theoretical Approach," Proc. Int'l Conf. Machine Learning, pp. 21-29, 1997.
    • (1997) Proc. Int'l Conf. Machine Learning , pp. 21-29
    • Auer, P.1
  • 18
    • 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," Proc. Int'l Conf. Machine Learning, pp. 341-349, 1998.
    • (1998) Proc. Int'l Conf. Machine Learning , pp. 341-349
    • Maron, O.1    Ratan, A.L.2
  • 20
    • 35148890331 scopus 로고    scopus 로고
    • Multiple instance learning of pulmonary embolism detection with geodesic distance along vascular structure
    • J. Bi and J. Liang, "Multiple Instance Learning of Pulmonary Embolism Detection with Geodesic Distance Along Vascular Structure," Proc. IEEE CS Conf. Computer Vision and Pattern Recognition, 2007.
    • (2007) Proc. IEEE CS Conf. Computer Vision and Pattern Recognition
    • Bi, J.1    Liang, J.2
  • 25
    • 0002629270 scopus 로고
    • Maximum likelihood from incomplete data via the em algorithm
    • A. Dempster, N. Laird, and D. Rubin, "Maximum Likelihood from Incomplete Data via the EM Algorithm," J. Royal Statistical Soc., vol.39, no.1, pp. 1-38, 1977.
    • (1977) J. Royal Statistical Soc. , vol.39 , Issue.1 , pp. 1-38
    • Dempster, A.1    Laird, N.2    Rubin, D.3
  • 34
    • 45349097640 scopus 로고    scopus 로고
    • Universal and adapted vocabularies for generic visual categorization
    • July
    • F. Perronnin, "Universal and Adapted Vocabularies for Generic Visual Categorization," IEEE Trans. Pattern Analysis and Machine Intelligence, vol.30, no.7, pp. 1243-1256, July 2008.
    • (2008) IEEE Trans. Pattern Analysis and Machine Intelligence , vol.30 , Issue.7 , pp. 1243-1256
    • Perronnin, F.1
  • 38
    • 0345414182 scopus 로고    scopus 로고
    • Video google: A text retrieval approach to object matching in videos
    • J. Sivic and A. Zisserman, "Video Google: A Text Retrieval Approach to Object Matching in Videos," Proc. Int'l Conf. Computer Vision (ICCV), pp. 1470-1477, 2003.
    • (2003) Proc. Int'l Conf. Computer Vision (ICCV) , pp. 1470-1477
    • Sivic, J.1    Zisserman, A.2
  • 39
    • 0001172265 scopus 로고
    • Learning logical definitions from relations
    • J.R. Quinlan, "Learning Logical Definitions from Relations," Machine Learning, vol.5, pp. 239-266, 1990.
    • (1990) Machine Learning , vol.5 , pp. 239-266
    • Quinlan, J.R.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.