Difference between revisions of "Winter 2018 CS595I Advanced NLP/ML Seminar"
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| + | * [VIVEK] Poincare Embeddings for learning Hierarchical Representations, Maximilian Nickel Douwe Kiela https://arxiv.org/pdf/1705.08039.pdf | ||
* Mimicking Word Embeddings using Subword RNNs, Yuval Pinter, Robert Guthrie and Jacob Eisenstein http://aclweb.org/anthology/D17-1010 | * Mimicking Word Embeddings using Subword RNNs, Yuval Pinter, Robert Guthrie and Jacob Eisenstein http://aclweb.org/anthology/D17-1010 | ||
Revision as of 16:58, 3 January 2018
Time: TBD Location: HFH 1132.
If you registered this class, you should contact the instructor to lead the discussion of one paper below. If you don't lead the discussion, you will then need to write a 2-page final report in ICML 2018 style, comparing any two of the papers below. Due: TBD to william@cs.ucsb.edu.
Contents
Word Embeddings
- [VIVEK] Poincare Embeddings for learning Hierarchical Representations, Maximilian Nickel Douwe Kiela https://arxiv.org/pdf/1705.08039.pdf
- Mimicking Word Embeddings using Subword RNNs, Yuval Pinter, Robert Guthrie and Jacob Eisenstein http://aclweb.org/anthology/D17-1010
Relational Learning and Reasoning
- Adversarial Training for Relation Extraction, Yi Wu, David Bamman and Stuart Russell https://people.eecs.berkeley.edu/~russell/papers/emnlp17-relation.pdf
Reinforcement Learning
- Robust Imitation of Diverse Behaviors, Wang et al. 2017, https://arxiv.org/pdf/1707.02747.pdf
- Programmable Agents, Denil et al., https://arxiv.org/pdf/1706.06383v1.pdf
- Expected Policy Gradients, Kamil Ciosek, Shimon Whiteson, https://arxiv.org/abs/1706.05374
- Reinforcement Learning with Deep Energy-Based Policies Haarnoja et al, ICML 2017 http://proceedings.mlr.press/v70/haarnoja17a/haarnoja17a.pdf
- Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning, Gu et al., NIPS 2017 https://arxiv.org/abs/1706.00387
- Sequence Level Training with Recurrent Neural Networks https://arxiv.org/pdf/1511.06732.pdf
Generation
- Adversarially Regularized Autoencoders for Generating Discrete Structures, Zhao et al., https://arxiv.org/pdf/1706.04223.pdf
Dialog
- A Deep Reinforcement Learning Chatbot, Serban et al., https://arxiv.org/pdf/1709.02349.pdf
NLP for Computational Social Science
- Analyzing Language in Fake News and Political Fact-Checking, Hannah Rashkin, Eunsol Choi, Jin Yea Jang, Svitlana Volkova and Yejin Choi https://www.cs.jhu.edu/~svitlana/papers/RCYVC_EMNLP2017.pdf
- Human Centered NLP with User Factor Adaptation. Veronica Lynn, Youngseo Son, Vivek Kulkarni, Niranjan Balasubramanian, H Andrew Schwartz, http://www.aclweb.org/anthology/D17-1120
