Deep learning to hash with multiple representations

Proceedings - IEEE International Conference on Data Mining, ICDM

Volumn , Issue , 2012, Pages 930-935

  Kang, Yoonseop ^a   Kim, Saehoon ^a   Choi, Seungjin ^a  

^a Pohang University of Science and Technology (POSTECH)   (South Korea)

Author keywords

Deep learning; Harmonium; Hashing; Multi view learning; Restricted Boltzmann machines

Indexed keywords

DEEP LEARNING; HARMONIUM; HASHING; MULTI-VIEW LEARNING; RESTRICTED BOLTZMANN MACHINE;

HAMMING DISTANCE;

DATA MINING;

EID: 84874039473     PISSN: 15504786     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDM.2012.24     Document Type: Conference Paper

References (22)

1. A. Gionis, P. Indyk, and R. Motawani, "Similarity search in high dimensions via hashing," in Proceedings of the International Conference on Very Large Data Bases (VLDB), 1999.
2. D. G. Lowe, "Distinctive image features from scale-invariant keypoints," International Journal of Computer Vision, vol. 60, no. 2, pp. 91-110, 2004.
3. A. Oliva and A. Torralba, "Modeling the shape of the scene: A holistic representation of the spatial envelope," International Journal of Computer Vision, vol. 42, no. 3, pp. 145-175, 2001.
4. N. Dalal and B. Triggs, "Histograms of oriented gradients for human detection," in Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), San Diego, CA, 2005.
5. M. Datar, N. Immorlica, P. Indyk, and V. Mirrokni, "Locality sensitive hashing scheme based on p-stable distributions," in Proceedings of the Annual ACM Symposium on Computational Geometry (SoCG), 2004.
6. A. Torralba, R. Fergus, and Y. Weiss, "Small codes and large image databases for recognition," in Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Anchorage, Alaska, 2008.
7. Y. Weiss, A. Torralba, and R. Fergus, "Spectral hashing," in Advances in Neural Information Processing Systems (NIPS), vol. 20. MIT Press, 2008.
8. R. Salakhutdinov and G. Hinton, "Semantic hashing," in Proceeding of the SIGIR Workshop on Information Retrieval and Applications of Graphical Models, 2007.
9. J. Wang, S. Kumar, and S. F. Chang, "Semi-supervised hashing for scalable image retrieval," in Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), San Francisco, CA, 2010.
10. S. Kim and S. Choi, "Semi-supervised discriminant hashing," in Proceedings of the IEEE International Conference on Data Mining (ICDM), Vancouver, Canada, 2011.
11. D. Zhang, F. Wang, and L. Si, "Composite hashing with multiple information sources," in Proceedings of the ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), Beijing, China, 2011.
12. J. Ngiam, A. Khosla, M. Kim, J. Nam, H. Lee, and A. Y. Ng, "Multimodal deep learning," in Proceedings of the International Conference on Machine Learning (ICML), Bellevue, WA, 2011.
13. Y. Kang and S. Choi, "Restricted deep belief networks for multi-view learning," in Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), Athens, Greece, 2011.
14. D. R. Hardoon, S. Szedmak, and J. Shawe-Taylor, "Canonical correlation analysis: An overview with applications to learning methods," Neural Computation, vol. 16, pp. 2639-2664, 2004.
15. E. P. Xing, R. Yan, and A. G. Hauptmann, "Mining associated text and images with dual-wing harmonium," in Proceedings of the Annual Conference on Uncertainty in Artificial Intelligence (UAI), Edinburgh, UK, 2005.
16. H. Lee and S. Choi, "Group nonnegative matrix factorization for EEG classification," in Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS), Clearwater Beach, Florida, 2009.
17. M. Salzmann, C. H. Ek, R. Urtasun, and T. Darrell, "Factorized orthogonal latent spaces," in Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS), Sardinia, Italy, 2010.
18. M. Welling, M. Rosen-Zvi, and G. Hinton, "Exponential family harmoniums with an application to information retrieval," in Advances in Neural Information Processing Systems (NIPS), vol. 17. MIT Press, 2005.
19. G. E. Hinton, "Training products of experts by minimizing contrastive divergence," Neural Computation, vol. 14, no. 8, pp. 1771-1800, 2002.
20. R. Salakhutdinov and G. Hinton, "Learning a nonlinear embedding by preserving class neighbourhood structure," in Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS), San Juan, Puerto Rico, 2007.
21. G. Griffin, A. Holub, and P. Perona, "Caltech-256 object category dataset," Caltech, Tech. Rep., 2007.
22. T. S. Chua, J. Tang, R. Hong, H. Li, Z. Luo, and Y. Zheng, "NUS-WIDE: a real-world web image database from national university of singapore," in Proceedings of the ACM International Conference on Image and Video Retrieval (CIVR), Santorini, Greece, 2009.