Semi-supervised classification using linear neighborhood propagation

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

Volumn 1, Issue , 2006, Pages 160-167

  Wang, Fei ^a   Wang, Jingdong ^b   Zhang, Changshui ^a   Shen, Helen C ^b  

^a TSINGHUA UNIVERSITY   (China)

^b HONG KONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

CONSTRAINED LEAST SQUARES; DATA RANKING; LINEAR NEIGHBORHOOD PROPAGATION (LNP); SEMI SUPERVISED CLASSIFICATION;

COMPUTATIONAL GEOMETRY; CONSTRAINT THEORY; IMAGE SEGMENTATION; LEAST SQUARES APPROXIMATIONS; LINEAR SYSTEMS; OBJECT RECOGNITION; OPTIMIZATION; PROBLEM SOLVING;

CLASSIFICATION (OF INFORMATION);

EID: 33845581114     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2006.272     Document Type: Conference Paper

References (30)

1. A. Blum, S. Chawla. Learning from Labeled and Unlabeled Data using Graph Mincuts. ICML. 2001.
2. D. Zhou, O. Bousquet, T. N. Lal, J. Weston, B. Schölkopf. Learning with Local and Global Consistency. NIPS. 2003.
3. O. Chapelle, J. Weston, B. Schölkopf. Cluster Kernels for Semi-Supervised Learning. NIPS. 2002.
4. M. Szummer, T. Jaakkola. Partially Labeled Classification with Markov Random Walks. NIPS. 2001.
5. M. Belkin, P. Niyogi, V. Sindhwani. On Manifold Regularization. AISTATS. 2005.
6. T. Joachims. Transductive Inference for Text Classification using Support Vector Machines. ICML. 1999.
7. S.T. Roweis and L.K. Saul, Noninear Dimensionality Reduction by Locally Linear Embedding. Science: vol. 290, 2323-2326. 2000.
8. L. K. Saul and S. T. Roweis. Think Globally, Fit Locally: Unsupervised Learning of Low Dimensional Manifolds. Journal of Machine Learning Research: vol. 4, 119-155. 2003.
9. J.B. Tenenbaum, V. de Silva, and J.C. Langford. A Global Geometric Framework for Nonlinear Dimensionality Reduction. Science: vol. 290, 2319-2323. 2000.
10. M. Belkin, P. Niyogi. Laplacian Eigenmaps and Spectral Techniques for Embedding and Clustering. NIPS. 2001.
11. P. Perona, J. Malik. Scale-Space and Edge Detection Using Anisotropic Diffusion. IEEE TPAMI: 12(7). 1990.
12. M. Belkin, I. Matveeva, P. Niyogi. Regularization and semisupervised learning on large graphs. COLT. 2004.
13. X. Zhu, Z. Ghahramani, J. Lafferty. Semi-supervised learning using Gaussian fields and harmonic functions. ICML. 2003.
14. D. Zhou and B. Schölkopf. Regularization on Discrete Spaces. DAGM 2005.
15. D. Zhou, J. Weston, A. Gretton, O. Bousquet, B. Schölkopf. Ranking on Data Manifolds. NIPS. 2003.
16. M. Belkin, P. Niyogi. Semi-Supervised Learning on Riemannian Manifolds. Machine Learning, 56, 209-239.
17. S. D. Kamvar, D. Klein, C. D. Manning. Spectral Learning. IJCAI. 2003.
18. O. Delalleu, Y. Bengio, & N. Le Roux. Non-Parametric Function Induction in Semi-Supervised Learning. AISTATS 2005.
19. F. Samaria, A. Harter. Parameterisation of a stochastic model for human face identification. Proc. of the 2nd IEEE Workshop on Applications of Computer Vision. 1994.
20. M. A. Turk and A. P. Pentland. Eigenfaces for recognition. Journal of Cognitive. Neuroscience, 3(1): 71-96, 1991.
21. P. N. Belhumeur, J. P. Hespanha, D. J. Kriegman. Eigenface vs. Fisherface: Recognition Using Class Specific Linear Projection. IEEE TPAMI. 19(7): 711-720, 1997.
22. M.-H. Yang. Kernel Eigenfaces vs. Kernel Fisherfaces: Face Recognition Using Kernel Methods. FGR. 2002.
23. S. A. Nene, S. K. Nayar and H. Murase. Columbia Object Image Library (COIL-20). Technical Report CUCS-005-96, February 1996.
24. F. Wang, J. Wang, C. Zhang. Spectral Feature Analysis. IJCNN. 2005.
25. T. B. Sebastian, P. N. Klein, B. B. Kimia. Recognition of Shapes by Editing Shock Graphs. ICCV. 2001.
26. Y. Boykov, M. P. Jolly. Interactive Graph Cuts for Optimal Boundary and Region Segmentation of Objects in N-D Images. ICCV. 2001.
27. L. Grady. Mutilabel Random Walker Image Segmentation Using Prior Models. CVPR. 2005.
28. Y. Li, J. Sun, C.-K. Tang and H.-Y. Shum. Lazy Snapping. ACM Transaction on Graphics: Vol 23, No. 3. 2004.
29. S. Barre. http://www.barre.nom.fr/medical/samples.
30. Q. WU. W. Dou, Y. Chen and J. Constans. Fuzzy Segementaion of Cerebral Tumorous Tissues in MR Images via Support Vector Machine and Fuzzy Clustering. IFSA. 2005.