[ICLR19] ORDERED NEURONS: INTEGRATING TREE STRUCTURES INTO RECURRENT NEURAL NETWORKS
本篇是ICLR2019的两篇Best Paper之一。另外一篇：THE LOTTERY TICKET HYPOTHESIS： FINDING SPARSE, TRAINABLE NEURAL NETWORKS算法 ABSTRACT 天然语言是分层结构的：较小的单元(例如短语)嵌套在较大的单元(例如子句)中。当较大的组件结束时，嵌套在其中的全部较小的组件也必须关闭。虽然标准的LSTM体系结构容许不一
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相关文章
- 1. [ICLR19] ORDERED NEURONS: INTEGRATING TREE STRUCTURES INTO RECURRENT NEURAL NETWORKS
- 2. (zhuan) Recurrent Neural Network
- 3. 读书笔记26：adding attentiveness to the neurons in recurrent neural networks
- 4. [ICLR2017]Tree-Structured Deconding with Doubly-Recurrent Neural Networks
- 5. [ICLR19] THE LOTTERY TICKET HYPOTHESIS： FINDING SPARSE, TRAINABLE NEURAL NETWORKS
- 6. The Unreasonable Effectiveness of Recurrent Neural Networks
- 7. Attention and Augmented Recurrent Neural Networks
- 8. 019 Recurrent Neural Networks
- 9. RNN(Recurrent Neural Networks)
- 10. Recurrent Neural Networks