Seminar participants will take turns presenting papers of their choice, with up to two papers being presented each week. Unless otherwise noted, all seminars are held in the Network Science Lab (Bldg 434, room 122) at 1:00 pm on Mondays.
Winter 2019 will focus on causal inference. A reading list has been posted on Gauchospace.
Enrollment code (CMPSC 595J): 09233 (Instructor: Ambuj Singh)
|Seminar Overview||Prof. Ambuj Singh|
|Causal inference in statistics: An overview, J. Pearl, Statistics Surveys Vol. 3 (2009) 96–146||Yuning Shen|
|Types of Causality and the do operator||Prof. Ambuj Singh|
|Causal inference in statistics: An overview, (continued from Jan 28)||Richika Sharan|
|Causal inference in statistics: An overview, (continued from Feb 4)||David Bernadett|
|"Causal Inference," from Advanced Data Analysis from an Elementary Point of View, by Shalizi.||Vania Wang and Archana Rajendran|
|"Causal Inference," from Advanced Data Analysis from an Elementary Point of View, by Shalizi.||Chandana Upadhyaya|
|Chapter 1, Actual Causailty, by Halpern.||Aneesha Mathur|
|Chapter 2, Actual Causailty, by Halpern.||Adam Schmidt|
|Twitter Sentiment Analysis: How to Hedge Your Bets in the Stock Markets, by Rao and Srivastava.||James Bird|
|Chapter 9, Statistical Analysis of fMRI Data, by Ashby.||Sikun Lin|
|Identification of causal effects using instrumental variables, by Angrist, Imbens, and Rubin.||Kevin Smith|
|Economic shocks and civil conflict: An instrumental variables approach, by Satyanath and Sergenti.||Su Burtner|