Transfer Learning Toolkit: Primers and Benchmarks

F. Zhuang, Z. Qi, K. Duan, D. Xi, Y. Zhu, H. Zhu, H. Xiong, and Q. He, “A comprehensive survey on transfer learning,” 2019, arXiv:1911.02685v1

Original

1911

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F. Zhuang, P. Luo, P. Yin, Q. He, and Z. Shi, “Concept learning for cross-domain text classification: A general probabilistic framework,” in Proc. 23rd International Joint Conference on Artificial Intelligence

1966

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J. Blitzer, R. McDonald, and F. Pereira, “Domain adaptation with structural correspondence learning,” in Proc. Conference on Empirical Methods in Natural Language Processing

2006

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W. Dai, Q. Yang, G. Xue, and Y. Yu, “Boosting for transfer learning,” in Proc. 24th International Conference on Machine Learning

2007

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J. Gao, W. Fan, J. Jiang, and J. Han, “Knowledge transfer via multiple model local structure mapping,” in Proc. 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

2008

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S.J. Pan and Q. Yang, “A survey on transfer learning,” IEEE Trans. Knowl. Data Eng

2010

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F. Zhuang, P. Luo, Z. Shen, Q. He, Y. Xiong, Z. Shi, and H. Xiong, “Collaborative Dual-PLSA: Mining distinction and commonality across multiple domains for text classification,” in Proc. 19th ACM International Conference on Information and Knowledge Management

2010

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S.J. Pan, X. Ni, J.-T. Sun, Q. Yang, and Z. Chen, “Cross-domain sentiment classification via spectral feature alignment,” in Proc. 19th International Conference on World Wide Web

2010

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F. Zhuang, P. Luo, H. Xiong, Q. He, Y. Xiong, and Z. Shi, “Exploiting associations between word clusters and document classes for cross-domain text categorization,” Stat. Anal. Data Min

2011

Cited alongside, same era.

X. Glorot, A. Bordes, and Y. Bengio, “Domain adaptation for large-scale sentiment classification: A deep learning approach,” in Proc. 28th International Conference on Machine Learning

2011

Cited alongside, same era.

S.J. Pan, I.W. Tsang, J.T. Kwok, and Q. Yang, “Domain adaptation via transfer component analysis,” IEEE Trans. Neural Netw

2011

Cited alongside, same era.

M. Chen, Z. Xu, K. Weinberger, and F. Sha, “Marginalized denoising autoencoders for domain adaptation,” in Proc. 29th International Conference on Machine Learning

2012

Cited alongside, same era.

M. Long, J. Wang, G. Ding, J. Sun, and P.S. Yu, “Transfer feature learning with joint distribution adaptation,”in Proc. IEEE International Conference on Computer Vision

Y. Ganin and V. Lempitsky, “Unsupervised domain adaptation by backpropagation,” in Proc. 32nd International Conference on Machine Learning

2015

Later among the works it cites.

F. Zhuang, X. Cheng, P. Luo, S.J. Pan, and Q. He, “Supervised representation learning: Transfer learning with deep autoencoders,” in Proc. 24th International Joint Conference on Artificial Intelligence

2015

Later among the works it cites.

B. Sun and K. Saenko, “Deep CORAL: Correlation alignment for deep domain adaptation,” in Proc. European Conference on Computer Vision Workshops

2016

Later among the works it cites.

Y. Ganin, E. Ustinova, H. Ajakan, P. Germain, H. Larochelle, F.¸Laviolette, M. Marchand, and V. Lempitsky, “Domain-adversarial training of neural networks,” J. Mach. Learn. Res

2016

Later among the works it cites.

C. Tan, F. Sun, T. Kong, W. Zhang, C. Yang, and C. Liu, “A Survey on deep transfer learning,” in Proc. 27th International Conference on Artificial Neural Networks