Deep linear coding for fast graph clustering

IJCAI International Joint Conference on Artificial Intelligence

Volumn 2015-January, Issue , 2015, Pages 3798-3804

  Shao, Ming ^a   Li, Sheng ^a   Ding, Zhengming ^a   Fu, Yun ^a  

^a NORTHEASTERN UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; CLUSTERING ALGORITHMS; CODES (SYMBOLS); DATA MINING;

BENCHMARK DATASETS; CLUSTERING ACCURACY; DATA MINING PROBLEMS; EIGEN DECOMPOSITION; FEATURE TRANSFORM; GRAPH CLUSTERING; LOCAL DISTORTION; SPECTRAL CLUSTERING;

BUILDING CODES;

EID: 84949788633     PISSN: 10450823     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (27)

1. Horace Barlow. Unsupervised learning. Neural Computation, 1(3):295-311, 1989.
2. Yoshua Bengio, Pascal Lamblin, Dan Popovici, Hugo Larochelle, et al. Greedy layer-wise training of deep networks. Advances in Neural Information Processing Systems, 19:153, 2007.
3. Yoshua Bengio, Aaron Courville, and Pascal Vincent. Representation learning: A review and new perspectives. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(8):1798-1828, 2013.
4. Yoshua Bengio. Learning deep architectures for ai. Foundations and Trends® in Machine Learning, 2(1):1-127, 2009.
5. Xinlei Chen and Deng Cai. Large scale spectral clustering with landmark-based representation. In AAAI Conference on Artificial Intelligence, 2011.
6. Wen-Yen Chen, Yangqiu Song, Hongjie Bai, Chih-Jen Lin, and Edward Y Chang. Parallel spectral clustering in distributed systems. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33(3):568-586, 2011.
7. Minmin Chen, Zhixiang Xu, Kilian Weinberger, and Fei Sha. Marginalized denoising autoencoders for domain adaptation. In International Conference on Machine Learning, 2012.
8. Fan RK Chung. Spectral graph theory, volume 92. American Mathematical Soc, 1997.
9. Jeffrey Dean, Greg Corrado, Rajat Monga, Kai Chen, Matthieu Devin, Mark Mao, Andrew Senior, Paul Tucker, Ke Yang, Quoc V Le, et al. Large scale distributed deep networks. In Advances in Neural Information Processing Systems, pages 1223-1231, 2012.
10. Inderjit S Dhillon, Yuqiang Guan, and Brian Kulis. Kernel k-means: spectral clustering and normalized cuts. In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 551-556. ACM, 2004.
11. Carl Eckart and Gale Young. The approximation of one matrix by another of lower rank. Psychometrika, 1(3):211-218, 1936.
12. Charless Fowlkes, Serge Belongie, Fan Chung, and Jitendra Malik. Spectral grouping using the nystrom method. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(2):214-225, 2004.
13. John A Hartigan and Manchek A Wong. Algorithm as 136: A k-means clustering algorithm. Applied Statistics, pages 100-108, 1979.
14. Trevor Hastie, Robert Tibshirani, Jerome Friedman, T Hastie, J Friedman, and R Tibshirani. The elements of statistical learning, volume 2. Springer, 2009.
15. Geoffrey Hinton, Simon Osindero, and Yee-Whye Teh. A fast learning algorithm for deep belief nets. Neural Computation, 18(7):1527-1554, 2006.
16. Peihao Huang, Yan Huang, Wei Wang, and Liang Wang. Deep embedding network for clustering. In International Conference on Pattern Recognition, pages 1532-1537. IEEE, 2014.
17. Anil K Jain, M Narasimha Murty, and Patrick J Flynn. Data clustering: a review. ACM Computing Surveys (CSUR), 31(3):264-323, 1999.
18. Honglak Lee, Alexis Battle, Rajat Raina, and Andrew Y Ng. Efficient sparse coding algorithms. In Advances in Neural Information Processing Systems, pages 801-808, 2006.
19. Marina Meila and Jianbo Shi. A random walks view of spectral segmentation. In International Workshop on Artificial Intelligence and Statistics, 2001.
20. Marius Muja and David Lowe. Scalable nearest neighbour algorithms for high dimensional data. IEEE Transactions on Pattern Analysis and Machine Intelligence, 36(11):2227-2240, 2014.
21. Andrew Y Ng, Michael I Jordan, Yair Weiss, et al. On spectral clustering: Analysis and an algorithm. Advances in Neural Information Processing Systems, 2:849-856, 2002.
22. Jianbo Shi and Jitendra Malik. Normalized cuts and image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(8):888-905, 2000.
23. Chunfeng Song, Feng Liu, Yongzhen Huang, Liang Wang, and Tieniu Tan. Auto-encoder based data clustering. In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, pages 117-124. Springer, 2013.
24. Fei Tian, Bin Gao, Qing Cui, Enhong Chen, and Tie-Yan Liu. Learning deep representations for graph clustering. In AAAI Conference on Artificial Intelligence, 2014.
25. Ulrike Von Luxburg. A tutorial on spectral clustering. Statistics and Computing, 17(4):395-416, 2007.
26. Donghui Yan, Ling Huang, and Michael I Jordan. Fast approximate spectral clustering. In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 907-916. ACM, 2009.
27. Jianchao Yang, Kai Yu, Yihong Gong, and Thomas Huang. Linear spatial pyramid matching using sparse coding for image classification. In IEEE Conference on Computer Vision and Pattern Recognition, pages 1794-1801. IEEE, 2009.