Multiple instance learning for soft bags via top instances

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn 07-12-June-2015, Issue , 2015, Pages 4277-4285

  Li, Weixin ^a   Vasconcelos, Nuno ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); COMPUTER VISION; LEARNING SYSTEMS; VECTOR SPACES;

EMPIRICAL EVALUATIONS; LARGE MARGINS; LATENT SUPPORT VECTOR MACHINES; MOST LIKELY; MULTIPLE INSTANCE LEARNING; NEGATIVE INSTANCES; POSITIVE INSTANCES; TRAINING SAMPLE;

PATTERN RECOGNITION;

EID: 84959247149     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2015.7299056     Document Type: Conference Paper

References (31)

1. S. Andrews, I. Tsochantaridis, and T. Hofmann. Support vector machines for multiple-instance learning. NIPS, 2002
2. S. Boyd and L. Vandenberghe. Convex optimization. 2004
3. R. C. Bunescu and R. J. Mooney. Multiple instance learning for sparse positive bags. ICML, 2007
4. G. Carneiro, A. B. Chan, P. J. Moreno, and N. Vasconcelos. Supervised learning of semantic classes for image annotation and retrieval. IEEE TPAMI, 29(3):394-410, 2007
5. Y. Chen, J. Bi, and J. Z. Wang. Miles: Multipleinstance learning via embedded instance selection. IEEE TPAMI, 28(12):1931-1947, 2006
6. Y. Chen and J. Z. Wang. Image categorization by learning and reasoning with regions. JMLR, 2004
7. J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei. Imagenet: A large-scale hierarchical image database. CVPR, 2009
8. T. Deselaers and V. Ferrari. A conditional random field for multiple-instance learning. ICML, 2010
9. T. Dietterich, R. Lathrop, and T. Lozano-Pérez. Solving the multiple instance problem with axis-parallel rectangles. Artificial Intelligence, 89(1-2):31-71, 1997
10. P. Felzenszwalb, R. Girshick, D. McAllester, and D. Ramanan. Object detection with discriminatively trained part-based models. IEEE TPAMI, 32(9):1627-1645, 2009
11. T. Gartner, P. A. Flach, A. Kowalczyk, and A. J. Smola. Multi-instance kernels. ICML, 2002
12. Y. Han, Q. Tao, and J. Wang. Avoiding false positive in multi-instance learning. NIPS, 2010
13. A. Joulin and F. Bach. A convex relaxation for weakly supervised classifiers. ICML, 2012
14. K. Kiwiel. Proximity control in bundle methods for convex nondifferentiable minimization. Mathematical Programming, 46:105-122, 1990
15. J. T. Kwok and P.-M. Cheung. Marginalized multiinstance kernels. IJCAI, 2007
16. O. Maron and A. L. Ratan. Multiple-instance learning for natural scene classification. ICML, 1998
17. D. Parikh and K. Grauman. Relative attributes. ICCV, 2011
18. S. Ray and M. Craven. Supervised versus multiple instance learning: An empirical comparison. ICML, 2005
19. Y.-Y. Sun, Y. Zhang, and Z.-H. Zhou. Multi-label learning with weak label. AAAI, 2010
20. I. Tsochantaridis, T. Hofmann, T. Joachims, and Y. Altun. Large margin methods for structured and interdependent output variables. JMLR, 6:1453-1484, 2005
21. N. Turakhia and D. Parikh. Attribute dominance: What pops out? ICCV, 2013
22. P. Viola, J. C. Platt, and C. Zhang. Multiple instance boosting for object detection. NIPS, 2005
23. C. Vondrick, D. Patterson, and D. Ramanan. Efficiently scaling up crowdsourced video annotation. Int J Comput Vis, 101(1):184-204, 2013
24. H.-Y. Wang, Q. Yang, and H. Zha. Adaptive pposterior mixture-model kernels for multiple instance learning. ICML, 2008
25. N. Weidmann, E. Frank, and B. Pfahringer. A twolevel learning method for generalized multi-instance problems. ECML, 2003
26. J. Xiao, J. Hays, K. A. Ehinger, A. Oliva, and A. Torralba. Sun database: Large-scale scene recognition from abbey to zoo. CVPR, 2010
27. A. L. Yuille and A. Rangarajan. The concave-convex procedure (cccp). NIPS, 2003
28. Q. Zhang and S. A. Goldman. Em-dd: An improved multiple-instance learning technique. NIPS, 2001
29. Q. Zhang, S. A. Goldman, W. Yu, and J. Fritts. Content-based image retrieval using multiple-instance learning. ICML, 2002
30. Z.-H. Zhou, Y.-Y. Sun, and Y.-F. Li. Multi-instance learning by treating instances as non-i. i. d. samples. ICML, 2009
31. Z.-H. Zhou and J.-M. Xu. On the relation between multi-instance learning and semi-supervised learning. ICML, 2007.