Difference between revisions of "Group Reading F16"
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| − | ** Improving Information Extraction by Acquiring External Evidence with Reinforcement Learning, Karthik Narasimhan, Adam Yala, Regina Barzilay. EMNLP 2016. https://arxiv.org/pdf/1603.07954v3.pdf | + | ** Presenter: Metehan Ozten: Improving Information Extraction by Acquiring External Evidence with Reinforcement Learning, Karthik Narasimhan, Adam Yala, Regina Barzilay. EMNLP 2016. https://arxiv.org/pdf/1603.07954v3.pdf |
| − | ** Learning to compose neural networks for question answering, Jacob Andreas, Marcus Rohrbach, Trevor Darrell and Dan Klein. NAACL 2016.https://arxiv.org/abs/1601.01705 | + | ** Presenter: Ke Ni: Learning to compose neural networks for question answering, Jacob Andreas, Marcus Rohrbach, Trevor Darrell and Dan Klein. NAACL 2016.https://arxiv.org/abs/1601.01705 |
| + | ** Some good EMNLP papers: | ||
| + | ***Rationalizing Neural Predictions, Tao Lei, Regina Barzilay, Tommi Jaakkola, https://arxiv.org/abs/1606.04155 | ||
| + | ***Deep Reinforcement Learning for Dialogue Generation, Jiwei Li, Will Monroe, Alan Ritter, Michel Galley, Jianfeng Gao, Dan Jurafsky, https://arxiv.org/abs/1606.01541 | ||
| + | ***Sequence-to-Sequence Learning as Beam-Search Optimization, Sam Wiseman and Alexander M. Rush, https://arxiv.org/pdf/1606.02960.pdf | ||
| + | ***Mining Inference Formulas by Goal-Directed Random Walks, Mining Inference Formulas by Goal-Directed Random Walks, https://www.aclweb.org/anthology/D/D16/D16-1145.pdf | ||
| + | |||
| + | *11/17: | ||
| + | ** Presenter: Daniel Auto-Encoding Variational Bayes, Kingma and Welling, ICLR 2014, https://arxiv.org/pdf/1312.6114v10.pdf | ||
| + | ** NEURAL ARCHITECTURE SEARCH WITH REINFORCEMENT LEARNING, ICLR 2017, http://openreview.net/pdf?id=r1Ue8Hcxg | ||
| + | |||
| + | *11/24: Thanksgiving. No Meeting. | ||
Latest revision as of 15:12, 10 November 2016
- 10/13:
- Presenter: William Wang, Random Walk Inference and Learning in A Large Scale Knowledge Base, Ni Lao, Tom Mitchell, William W. Cohen. http://www.cs.cmu.edu/~nlao/publication/2011/2011.emnlp.paper.pdf
- Presenter: Tyler Vuong, Translating Embeddings for Modeling Multi-relational Data Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran et al.,https://www.utc.fr/~bordesan/dokuwiki/_media/en/transe_nips13.pdf
- 10/20:
- Presenter: Thien Hoang, Compositional Vector Space Models for Knowledge Base Completion. Arvind Neelakantan, Benjamin Roth and Andrew McCallum. https://people.cs.umass.edu/~arvind/acl2015.pdf
- Presenter: Darren Huang, Relation Classification via Convolutional Deep Neural Network, Daojian Zeng, Kang Liu, Siwei Lai, Guangyou Zhou and Jun Zhao. http://www.aclweb.org/anthology/C14-1220
- 10/27:
- Presenter: Peter Zhe Fu, GANs: Generative Adversarial Networks, Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, Yoshua Bengio. https://arxiv.org/abs/1406.2661
- Presenter: Shaoyi Zhang, SeqGAN: SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient, Lantao Yu, Weinan Zhang, Jun Wang, Yong Yu, https://arxiv.org/abs/1609.05473
- 11/3: No meeting. EMNLP + midterm.
- 11/10:
- Presenter: Metehan Ozten: Improving Information Extraction by Acquiring External Evidence with Reinforcement Learning, Karthik Narasimhan, Adam Yala, Regina Barzilay. EMNLP 2016. https://arxiv.org/pdf/1603.07954v3.pdf
- Presenter: Ke Ni: Learning to compose neural networks for question answering, Jacob Andreas, Marcus Rohrbach, Trevor Darrell and Dan Klein. NAACL 2016.https://arxiv.org/abs/1601.01705
- Some good EMNLP papers:
- Rationalizing Neural Predictions, Tao Lei, Regina Barzilay, Tommi Jaakkola, https://arxiv.org/abs/1606.04155
- Deep Reinforcement Learning for Dialogue Generation, Jiwei Li, Will Monroe, Alan Ritter, Michel Galley, Jianfeng Gao, Dan Jurafsky, https://arxiv.org/abs/1606.01541
- Sequence-to-Sequence Learning as Beam-Search Optimization, Sam Wiseman and Alexander M. Rush, https://arxiv.org/pdf/1606.02960.pdf
- Mining Inference Formulas by Goal-Directed Random Walks, Mining Inference Formulas by Goal-Directed Random Walks, https://www.aclweb.org/anthology/D/D16/D16-1145.pdf
- 11/17:
- Presenter: Daniel Auto-Encoding Variational Bayes, Kingma and Welling, ICLR 2014, https://arxiv.org/pdf/1312.6114v10.pdf
- NEURAL ARCHITECTURE SEARCH WITH REINFORCEMENT LEARNING, ICLR 2017, http://openreview.net/pdf?id=r1Ue8Hcxg
- 11/24: Thanksgiving. No Meeting.
