Difference between revisions of "Winter 2018 CS595I Advanced NLP/ML Seminar"

From courses
Jump to: navigation, search
Line 33: Line 33:
  
 
* 03/05
 
* 03/05
 +
** [Abhijit] Safe and Nested Subgame Solving for Imperfect-Information Games. Noam Brown, Tuomas Sandholm. https://nips.cc/Conferences/2017/Schedule?showEvent=8864
  
 
* 03/12
 
* 03/12
Line 57: Line 58:
 
===Learning===
 
===Learning===
 
* Variance-based Regularization with Convex Objectives. Hongseok Namkoong, John Duchi. https://arxiv.org/abs/1610.02581
 
* Variance-based Regularization with Convex Objectives. Hongseok Namkoong, John Duchi. https://arxiv.org/abs/1610.02581
* Safe and Nested Subgame Solving for Imperfect-Information Games. Noam Brown, Tuomas Sandholm. https://nips.cc/Conferences/2017/Schedule?showEvent=8864
 
  
 
===NLP for Computational Social Science===
 
===NLP for Computational Social Science===
 
*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
 
*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

Revision as of 16:18, 30 January 2018

Time: Monday 5-6pm, starting 01/22. Location: HFH 1132.

If you registered this class, you should contact the instructor to present one paper *and* be the discussant of one paper below.

  • Presenter: prepare a short summary of no more than 15 mins of presentation.
  • Discussant: by presenting a paper in one session, you automatically become the discussant of the other paper. Please prepare two questions for discussion about the paper.

If you don't present or 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.

  • 03/12

Reinforcement Learning

Generation

Learning

NLP for Computational Social Science