[1] Senatoe T E. Transfer Learning Progress and Potential[J]. AI Magazine, 2011, 32(1): 84-86. [2] Zhang Huxiang. Transfer Learning Throught Domain Adaptation[C]//Proceedings of the 8th International Symposium on Neural Networks. Guilin, China, [s. n.], 2011: 505-512. [3] Mei Shuyu, Wang Fei, Zhou Shuigeng. Gene Ontology Based Transfer Learning for Protein Subcellular Localization[J]. BMC Bioinformatics, 2011, 12(1): 44-54. [4] Chen Mingsan, Han Jiawei, Yu P S. Data Mining: An Overview from a Database Perspectiv[J]. IEEE Trans. on Knowledge and Data Engineering, 1996, 8(2): 866-883. [5] Sathish R I, Krishnaj S S, Narasimha S S, et al. A Fast Quasi- newton Method for Semi-supervised SVM[J]. Pattern Recognition, 2011, 44(1): 2305-2313. [6] Dai Wenyuan, Chen Yuqiang, Xue Guirong, et al. Translated Learning: Transfer Learning Across Different Feature Spaces[C]//Processing of NIPS’08. Vancouver, Canada: [s. n.], 2008: 353-360. [7] Dai Wenyuan, Yang Qiang, Xue Guirong, et al. Self-taught Clustering[C]//Proceedings of the 25th International Conference on Machine Learning. Helsinki, Finland: [s. n.], 2008: 200-207. [8] John S T, Bartlett P L, Williamson R C, et al. Structural Risk Minimization over Data-dependent Hierarchies[J]. IEEE Transactions on Information Theory, 1998, 44(2): 1926-1940. [9] Siwei L. Mercer Kernels for Object Recognition with Local Features[C]//Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Diego, USA: [s. n.], 2005: 223-229. [10] Wang Shitong, Chung K, Fu Lai, et al. A Novel Image Thres- holding Method Based on Parzen Window Estimate[J]. Pattern Recognition, 2008, 42(12): 117-129. [11] Li Xuelong, Pang Yanwei, Yuan Yuan. L1-norm-based 2DPCA[J]. IEEE Transactions on Systems, Man, and Cybernetics, 2010, 40(3): 1170-1175. [12] Jian Jinbao, Quan Ran, Cheng Weixin. A Feasible QP-free Algorithm Combining the Interior-point Method with Active Set for Constrained Optimization[J]. Computers Mathematics with Application, 2009, 58(9): 1520-1533. [13] Strum M, Wang Jiangu, Artur J, et al. The Multiple Pairs SMO: A Modified SMO Algorithm for the Acceleration of the SVM Training[C]//Proceedings of International Joint Conference on Neural Networks. Atlanta, USA: [s. n.], 2009: 1221-1228.
|