Part-based transfer learning

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6677 LNCS, Issue PART 3, 2011, Pages 434-441

  Xu, Zhijie ^a   Sun, Shiliang ^a  

^a EAST CHINA NORMAL UNIVERSITY   (China)

Author keywords

Machine learning; Part based modeling; Support vector machine; Transfer learning

Indexed keywords

COMPLEX TASK; LEARNING FRAMEWORKS; LEARNING STRATEGY; LEARNING TASKS; MACHINE-LEARNING; PART-BASED MODELING; SYNTHETIC DATA; TRANSFER LEARNING;

GEARS; SUPPORT VECTOR MACHINES;

NEURAL NETWORKS;

EID: 79957853570     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-21111-9_49     Document Type: Conference Paper

References (12)

1. Jin, F., Sun, S.: A multitask learning approach to face recognition based on neural networks. In: Proceedings of 9th International Conference on Intelligent Data Engineering and Automated Learning, pp. 24-31 (2008)
2. Chen, Q., Sun, S.: Hierarchical multi-view fisher discriminant analysis. In: Proceedings of 16th International Conference on Neural Information Processing, pp. 289-298 (2009)
3. Raina, R., Ng, A.Y., Koller, D.: Constructing informative priors using transfer learning. In: Proceedings of the 23rd International Conference on Machine Learning, pp. 713-720 (2006)
4. Wu, P., Dietterich, T.G.: Improving SVM accuracy by training on auxiliary data sources. In: Proceedings of the 21st International Conference on Machine Learning, p. 110 (2004)
5. 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, pp. 759-766 (2007)
6. Davis, J., Domingos, P.: Deep transfer via second-order Markov logic. In: Proceedings of the 26th Annual International Conference on Machine Learning, pp. 217-224 (2009)
7. Ross, D.A., Zemel, R.S.: Learning parts-based representations of data. Journal of Machine Learning Research 7, 2369-2397 (2006)
8. Felzenszwalb, P.F., Girshick, R.B., McAllester, D., Ramanan, D.: Object detection with discriminatively trained part based models. IEEE Transactions on Pattern Analysis and Machine Intelligence 32, 1627-1645 (2009)
9. Bar-Hillel, A., Hertz, T., Weinshall, D.: Object class recognition by boosting a part-based model. In: Proceedings of IEEE Computer Society Conference on Computer Vision and Recognition, vol. 1, pp. 702-709 (2005)
10. Dai, W., Yang, Q., Xue, G.R., Yu, Y.: Boosting for transfer learning. In: Proceedings of the 24th International Conference on Machine Learning, pp. 193-200 (2007)
11. Ben-David, S., Schuller, R.: Exploiting task relatedness for multiple task learning. In: Proceedings of the 6th Annual Conference on Learning Theory, pp. 567-580 (2003)
12. Lima, N.H.C., Neto, A.D.D., Melo, J.D.: Creating an ensemble of diverse support vector machines using Adaboost. In: Proceedings of the International Joint Conference on Neural Networks, pp. 2342-2346 (2009)