Difference between revisions of "Fall 2017 CS595I Advanced NLP/ML Seminar"

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*11/07:
 
*11/07:
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** Gavin: * Hindsight Experience Replay, Andrychowicz et al, https://arxiv.org/pdf/1707.01495.pdf
  
 
*11/14:
 
*11/14:
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* Programmable Agents, Denil et al., https://arxiv.org/pdf/1706.06383v1.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
 
* Expected Policy Gradients, Kamil Ciosek, Shimon Whiteson, https://arxiv.org/abs/1706.05374
* Hindsight Experience Replay, Andrychowicz et al, https://arxiv.org/pdf/1707.01495.pdf
 
 
* Reinforcement Learning with Deep Energy-Based Policies  Haarnoja et al, ICML 2017 http://proceedings.mlr.press/v70/haarnoja17a/haarnoja17a.pdf
 
* Reinforcement Learning with Deep Energy-Based Policies  Haarnoja et al, ICML 2017 http://proceedings.mlr.press/v70/haarnoja17a/haarnoja17a.pdf
 
* Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation, Kulkarni et al., 2016, https://arxiv.org/pdf/1604.06057.pdf
 
* Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation, Kulkarni et al., 2016, https://arxiv.org/pdf/1604.06057.pdf

Revision as of 14:19, 9 October 2017

Time: Tuesday 5-6pm. 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 3-page final report in NIPS 2017 style, comparing any two of the papers below.

  • 09/26:
    • Mahnaz Summer research presentation: Reinforced Pointer-Generator Network for Abstractive Summarization.
    • Xin: FeUdal Networks for Hierarchical Reinforcement Learning, Vezhnevets et al., ICML 2017 https://arxiv.org/pdf/1703.01161.pdf
  • 11/14:
  • 11/28:
  • 12/05: No meeting, NIPS conference.
  • 12/12: No meeting, NAACL deadline.

Word Embeddings

Relational Learning and Reasoning

Reinforcement Learning

Learning (General)

Generation

Dialog

NLP for Computational Social Science