Open Access
| Issue |
ITM Web Conf.
Volume 12, 2017
The 4th Annual International Conference on Information Technology and Applications (ITA 2017)
|
|
|---|---|---|
| Article Number | 03043 | |
| Number of page(s) | 4 | |
| Section | Session 3: Computer | |
| DOI | https://doi.org/10.1051/itmconf/20171203043 | |
| Published online | 05 September 2017 | |
- Bengio Y, Lamblin P, Popovici D, et al. Greedy layer-wise training of deep networks[C]. Proc, of the 20th Annual Conference on Neural Information Processing System. 2006:153–160. [Google Scholar]
- Vincent p, Larochelle H, Bengio Y, Extracting and coin-posing robust features with denoising autoencoders[ C]. Proc. of the 25th International Conference on Machine Learning. 2008:1096–1103. [Google Scholar]
- Bengio Y. Learning deep architectures for Al[J]. Foundations and Trends in Machine Leaning, 2009,2(1):1–127. [Google Scholar]
- Salah R, Vincent P, Muller X, et al. Contractive autpencoders: Explicit invariance during feature extraction[C]. Proc. of the 28th International Conference on Machine Learning.2011:833–840. [EDP Sciences] [Google Scholar]
- J. Clerk Maxwell, A Treatise on Electricity and Magnetism, 3rd ed., vol. 2. Oxford: Clarendon, 1892, pp.68–73. [Google Scholar]
- Amaral T, Silva L M, Alexande L A, et al. Using different cost functions to train stacked auto_encoders[C]. Proc. of the 12th Mexican International Conference on Artificial Intelligence. 2013:114–120. [Google Scholar]
- Guyon I, Dror G, Leaire V, et al. Auto-encoders unsupervised learning and deep architectures[C]. Proc. of the 28th International Conference on Machine Learning. 2012:37–50 [Google Scholar]
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