Zhu Zhenfeng, Zhu Xingquan, Ye Yangdong, et al. Transfer active learning//Proceedings of the 20th ACM International Conference on Information and Knowledge Management. Glasgow: ACM, 2011: 2169-2172.
[2]
Zhu Yin, Chen Yuqiang, Lu Zhongqi, et al. Heterogeneous transfer learning for image classification//Proceedings of the 25th AAAI Conference on Artificial Intelli- gence. San Francisco: AAAI Press, 2011: 1304-1309.
[3]
Qi Guojun, Aggarwal C, Huang Thomas. Towards semantic knowledge propagation from text corpus to web images//Proceedings of the 20th International Conference on World Wide Web. Hyderabad: ACM Press, 2011: 297-306.
[4]
Muslea I, Minton S, Knoblock C A. Active+semi-supervised learning=robust multi-view learning//Proceedings of the 19th International Conference on Machine Learning. Sydney: ACM Press, 2002: 435-442.
[5]
Pan S J L, Yang Qiang. A Survey on transfer learning[J]. IEEE Transaction on Knowledge and Data Engineering, 2010, 22(10): 1345-1359.
[6]
Pan Jialin. Feature-based transfer learning with real-world application. Hong Kong: The Hong Kong University of Science and Technology, 2010.
[7]
Porteous I, Newman D, Ihler A, et al. Fast collapsed gibbs sampling for latent dirichlet allocation//Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Las Vegas: ACM Press, 2008: 569-577.
[8]
Bay H, Eelaars A, Gool L V. Speed-up robust features (SURF) [J]. Computer Vision and Image Understanding, 2008, 110(3): 346-359.
[9]
Li Feifei, Perona P. A bayesian hierarchical model for learning natural scene categories//Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Diego: IEEE Press, 2005: 524-531.