Please complete each homework for each team, and
mention who contributed which parts in your report.
NN with Memory can potentially to be used to acompplish many AI related tasks: Reasoning, Decision Making, etc.
Here are some related talks:
- Sumit Chopra from Facebook. Reasoning, Attention and Memory slides
- Edward Grefenstette from Google DeepMind. Beyond Seq2Seq with Augmented RNNs slides
- [+10] Please find a recent paper (2014-2015) which introduced a NN with memory.
- [+50] Write a report to briefly introduce the paper;
- [+40] then, focus on discussing the unique properties of the new NN and where it can be applied to take advantage of the properties.
- Search RNN on Arxiv-sanity link
- Jianpeng Cheng et al. Long Short-Term Memory-Networks for Machine Reading. arXiv16’.
- Nal Kalchbrenner et al. Grid Long Short-Term Memory. arXiv16’. (From DeepMind, Alex)
- Kaisheng Yao et al. Depth-Gated LSTM. arXiv15’.
- Shuohang Wang et al. Learning Natural Language Inference with LSTM. arXiv15’.
- Junyoung Chung et al. Gated Feedback Recurrent Neural Networks. arXiv15’.
- Due on Oct. 3rd before class.