Higher order learning with graphs

ACM International Conference Proceeding Series

Volumn 148, Issue , 2006, Pages 17-24

  Agarwal, Sameer ^a   Branson, Kristin ^a   Belongie, Serge ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGEBRA; GRAPH THEORY; PROBLEM SOLVING; TENSORS;

FORMULATIONS; HYPERGRAPHS; LEARNING PROBLEM; NATURAL TOOLS;

LEARNING ALGORITHMS;

EID: 34250754984     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1143844.1143847     Document Type: Conference Paper

References (23)

1. Agarwal, S., Lim, J., Zelnik-Manor, L., Perona, P., Kriegman, D. J., & Belongie, S. (2005). Beyond pairwise clustering. CVPR (2) (pp. 838-845).
2. Alpert, C. J., Kahng, A. B., & Yao, S.-Z. (1999). Spectral partitioning with multiple eigenvectors. Discrete Applied Mathematics, 90, 3-26.
3. Belkin, M., & Niyogi, P. (2003). Semi-supervised learning on riemannian manifolds. Mach. Learn., 56, 209-239.
4. Bolla, M. (1993). Spectra, euclidean representations and clusterings of hypergraphs. Discrete Mathematics, 117.
5. Chung, F. R. (1993). The Laplacian of a hypergraph. In J. Friedman (Ed.), Expanding graphs (DIMACS series), 21-36. AMS.
6. Chung, F. R. K. (1997). Spectral graph theory. AMS.
7. Forman, R. (2003). Bochner's method for cell complexes and combinatorial Ricci curvature. Discrete & Computational Geometry, 29, 323-374.
8. Gibson, D., Kleinberg, J. M., & Raghavan, P. (1998). Clustering categorical data: An approach based on dynamical systems. VLDB (pp. 311-322).
9. Govindu, V. M. (2005). A tensor decomposition for geometric grouping and segmentation. CVPR.
10. Li, W., & Solé, P. (1996). Spectra of regular graphs and hypergraphs and orthogonal polynomials. European Journal of Combinatorics, 17, 461-477.
11. Munkres, J. R. (1984). Elements of algebraic topology. The Benjamin/Cummings Publishing Company.
12. Ng, A., Jordan, M., & Weiss, Y. (2002). On spectral clustering: Analysis and an algorithm. NIPS.
13. Rodríguez, J. A. (2002). On the Laplacian eigenvalues and metric parameters of hypergraphs. Linear and Multilinear Algebra, 50, 1-14.
14. Rodríguez, J. A. (2003). On the Laplacian spectrum and walk-regular hypergraphs. Linear and Multilinear Algebra, 51, 285-297.
15. Rosenberg, S. (1997). The Laplacian on a Riemannian manifold. London Mathematical Society.
16. Shashua, A., & Hazan, T. (2005). Non-negative tensor factorization with applications to statistics and vision. ICML.
17. Shashua, A., Zass, R., & Hazan, T. (2006). Multi-way clustering using super-symmetric non-negative tensor factorization. ECCV.
18. Shi, J., & Malik, J. (2000). Normalized cuts and image segmentation. PAMI, 22, 888-905.
19. Smola, A., & Kondor, l. (2003). Kernels and regularization on graphs. COLT. Springer.
20. Zhou, D., Huang, J., & Schölkopf, B. (2005). Beyond pairwise classification and clustering using hypergraphs (Technical Report 143). Max Plank Institute for Biological Cybernetics, Tübingen, Germany.
21. Zhou, D., & Schölkopf, B. (2005). Regularization on discrete spaces. Pattern Recognition, 361-368.
22. Zhu, X. (2005). Semi-supervised learning literature survey (Technical Report 1530). Computer Sciences, University of Wisconsin.
23. Zien, J. Y., Schlag, M. D. F., & Chan, P. K. (1999). Multilevel spectral hypergraph partitioning with arbitrary vertex sizes. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 18, 1389-1399.