Discriminative Factor Alignment across Heterogeneous Feature Space
详细信息 查看全文
- 作者：Fangwei Hu (21)
Tianqi Chen (21)
Nathan N. Liu (22)
Qiang Yang (22)
Yong Yu (21) - 刊名：Lecture Notes in Computer Science
- 出版年：2012
- 出版时间：2012
- 年：2012
- 卷：7524
- 期：1
- 页码：773-788
- 全文大小：1038KB
- 参考文献：1. Pan, S.J., Yang, Q.: A survey on transfer learning. IEEE Transactions on Knowledge and Data Engineering聽22, 1345鈥?359 (2010) CrossRef
2. Yang, Q., Chen, Y., Xue, G.-R., Dai, W., Yu, Y.: Heterogeneous transfer learning for image clustering via the social web. In: Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: vol. 1, ACL 2009, pp. 1鈥?. Association for Computational Linguistics, Stroudsburg (2009)
3. Raina, R., Battle, A., Lee, H., Packer, B., Ng, A.Y.: Self-taught learning: transfer learning from unlabeled data. In: Proceedings of the 24th International Conference on Machine Learning, ICML 2007, pp. 759鈥?66. ACM, New York (2007) CrossRef
4. Dai, W., Chen, Y., Xue, G.R., Yang, Q., Yu, Y.: Translated learning: Transfer learning across different feature spaces (2008)
5. Zhu, Y., Chen, Y., Lu, Z., Pan, J.S., Xue, G.R., Yu, Y., Yang, Q.: Heterogeneous transfer learning for image classification (2011)
6. Duygulu, P., Barnard, K., de Freitas, J.F.G., Forsyth, D.: Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002, Part IV. LNCS, vol.聽2353, pp. 97鈥?12. Springer, Heidelberg (2002) CrossRef
7. Barnard, K., Duygulu, P., Forsyth, D., de Freitas, N., Blei, D.M., Jordan, M.I.: Matching words and pictures. J. Mach. Learn. Res.聽3, 1107鈥?135 (2003)
8. Blei, D.M., Jordan, M.I.: Modeling annotated data. In: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Informaion Retrieval, SIGIR 2003, pp. 127鈥?34. ACM, New York (2003) CrossRef
9. Lavrenko, V., Manmatha, R., Jeon, J.: A model for learning the semantics of pictures (2003)
10. Carneiro, G., Chan, A.B., Moreno, P.J., Vasconcelos, N.: Supervised learning of semantic classes for image annotation and retrieval. IEEE Transactions on Pattern Analysis and Machine Intelligence聽29(3), 394鈥?10 (2007) CrossRef
11. Makadia, A., Pavlovic, V., Kumar, S.: A New Baseline for Image Annotation. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part III. LNCS, vol.聽5304, pp. 316鈥?29. Springer, Heidelberg (2008) CrossRef
12. Jin, Y., Khan, L., Wang, L., Awad, M.: Image annotations by combining multiple evidence & wordnet. In: Proceedings of the 13th Annual ACM International Conference on Multimedia, MULTIMEDIA 2005, pp. 706鈥?15. ACM, New York (2005) CrossRef
13. Wang, C., Jing, F., Zhang, L., Zhang, H.-J.: Content-based image annotation refinement. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2007 (2007)
14. Liu, D., Hua, X.S., Wang, M., Zhang, H.J.: Image retagging. In: Proceedings of the International Conference on Multimedia, MM 2010, pp. 491鈥?00. ACM, New York (2010) CrossRef
15. Liu, D., Yan, S., Hua, X.-S., Zhang, H.-J.: Image retagging using collaborative tag propagation. IEEE Transactions on Multimedia聽13(4), 702鈥?12 (2011) CrossRef
16. Chen, Y., Jin, O., Xue, G.R., Chen, J., Yang, Q.: Visual contextual advertising: Bringing textual advertisements to images (2010)
17. Fei-Fei, L., Perona, P.: A bayesian hierarchical model for learning natural scene categories. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, vol.聽2, pp. 524鈥?31 (2005)
18. Rendle, S., Freudenthaler, C., Gantner, Z., Schmidt-Thieme, L.: Bpr: Bayesian personalized ranking from implicit feedback. In: Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence, UAI 2009, Arlington, Virginia, United States. AUAI Press (2009)
19. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision聽60, 91鈥?10 (2004) CrossRef
20. Sivic, J., Russell, B., Efros, A., Zisserman, A., Freeman, W.: Discovering object categories in image collections (2005)
21. Singh, A.P., Gordon, G.J.: Relational learning via collective matrix factorization. In: Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2008, pp. 650鈥?58. ACM, New York (2008) CrossRef - 作者单位：Fangwei Hu (21)
Tianqi Chen (21)
Nathan N. Liu (22)
Qiang Yang (22)
Yong Yu (21)
21. Shanghai Jiao Tong University, Shanghai, China
22. Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong
文摘
Transfer learning as a new machine learning paradigm has gained increasing attention lately. In situations where the training data in a target domain are not sufficient to learn predictive models effectively, transfer learning leverages auxiliary source data from related domains for learning. While most of the existing works in this area are only focused on using the source data with the same representational structure as the target data, in this paper, we push this boundary further by extending transfer between text and images. We integrate documents , tags and images to build a heterogeneous transfer learning factor alignment model and apply it to improve the performance of tag recommendation. Many algorithms for tag recommendation have been proposed, but many of them have problem; the algorithm may not perform well under cold start conditions or for items from the long tail of the tag frequency distribution. However, with the help of documents, our algorithm handles these problems and generally outperforms other tag recommendation methods, especially the non-transfer factor alignment model.