【文獻閱讀】Augmenting Supervised Neural Networks with Unsupervised Objectives-ICML-2016
一、Abstract 從近期對unsupervised learning 的研究得到啓發，在large-scale setting 上，本文把unsupervised learning 與supervised learning結合起來，提高了supervised learning的性能。主要是把autoencoder與CNN結合起來 二、Key words: SAE;SWWAE; reconstr
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相關文章
- 1. 文獻閱讀 - Binarized Neural Networks
- 2. 讀文獻——《ImageNet classification with deep convolutional neural networks》
- 3. 【文獻閱讀】Non-local Neural Networks
- 4. 【文獻閱讀】Self-Normalizing Neural Networks
- 5. Recurrent neural networks for multivariate time series with missing values文獻閱讀
- 6. 文獻閱讀（44）
- 7. 論文閱讀——Unsupervised Neural Machine Translation with Indirect Supervision
- 8. Weakly supervised object recognition with convolutional neural networks 論文解讀
- 9. 《Collaborative Filtering with Recurrent Neural Networks》閱讀
- 10. 文獻閱讀