Pan S J, Yang Q. A survey on transfer learning[J]. IEEE Trans on Knowledge and Data Engineering, 2010, 22(10): 1345-1359.
[2]
Tao J W, Chung F L, Wang S T. A kernel learning framework for domain adaptation learning[J]. Science China Information Sciences, 2012, 55(9): 1983-2007.
[3]
Tao J W, Chung F L, Wang S T. On minimum distribution discrepancy support vector machine for domain adaptation[J]. Pattern Recognition, 2012, 45(11): 3962-3984.
[4]
Pan S J, Kwok J T, Yang Q. Transfer learning via dimensionality reduction[C]. Proc of the 23rd National Conf on Artificial Intelligence. Menlo Park: AAAI Press, 2008: 677-682.
[5]
Xie S, Fan W, Peng J, et al. Latent space domain transfer between high dimensional overlapping distributions[C]. Proc of the 18th Int Conf on World Wide Web. New York: ACM Press, 2009: 91-100.
[6]
Dai W, Yang Q, Xue G, et al. Boosting for transfer learning[C]. Proc of the 24th Int Conf on Machine Learning. New York: ACM Press, 2007: 193-200.
(Chen D P. Knowledge transfer for cross domain learning to rank[D]. Hefei: School of Computer Science and Technology, University of Science and Technology of China, 2010.)
[11]
Vapnik V. The nature of statistical learning theory[M]. New York: Springer-Verlag, 1995: 123-167.
[12]
Pal M, Foody G M. Feature selection for classification of hyper spectral data by SVM[J]. IEEE Trans on Geoscience and Remote Sensing, 2010, 48(5): 2297-2307.
(Wang J, Wang S T, Wang X M. Double-indices fuzzy subspace clustering algorithm based on feature weighted distance[J]. Control and Decision, 2010, 25(8): 1207-1210.)
