Schedule

Thursday, September 24

Introduction, slides (pdf)

Assignment: Introduce yourself on the forum

 

Tuesday, September 29

Graphical Models, slides (pdf)

Reading:  Graphical Models in a Nutshell

Assignment: QCR #1, posted by start of class

 

Thursday, October 1

Pearl's Turing Award lection on Causality, video

Notes: Lise will be away.   We'll watch video in class together, and you all are welcome to discuss.   This gives a framework for the overall class, where we want to get to.   We will not be studying Pearl's do-calculus until a few weeks later in the class.  

 

Tuesday, October 6

Graphical Models continued, slides (pdf)

Assignment: Post an example of "good" and "bad" causal modeling on the Synthesis Documents, posted by start of class

 

Thursday, October 8

Hal Daume III talk, 4PM, E2 180

Algorithms that Learn to Think on their Feet

 

Tuesday, October 13

Causal Modeling in Statistics

Reading: Statisistics and Causal Inference (here is a local link, in case you have trouble accessing the pdf through the journal site)

Presenter: Jiaqi Wu

Assignment: QCR #2, posted by noon

 

Thursday, October 15

Potential Outcomes Models

Reading: Causal Inference Using Potential Outcomes  (updated link!)

Presenter: Pardis Miri

Assignment: QCR #3, posted by noon

 

Tuesday, October 20

Propensity Score Matching

Reading: The Central Role of the Propensity Score in Observational Studies for Causal Effects

Presenter: Keshav Mathur

Assignment: QCR #4, posted by noon

Structural Equation Models

Reading: Wikipedia entry + Selection from Morgan & Winship, Counterfactuals and Causal Inference (ch3), pdf 

Presenter: Dhanya Sridhar

Assignment: QCR #5, posted by noon

 

Thursday, October 22

Reading: Selection from Morgan & Winship, Counterfactuals and Causal Inference (ch4), pdf

Presenter: Ryan Compton

Assignment: QCR #6, posted by noon

 

Tuesday, October 27

Causal Modeling: Pearl

Reading: Causal Inference from Big Data: Theoretical Foundations and the Data Fusion Problem, Barienboim and Pearl, 

NAS 2015,  pdf

Presenter: Adam Summerville

Assignment: QCR #7, posted by noon, PROJECT PROPOSAL DUE

Please turn in 1-2 page project proposal in class.   Your project proposal should include a description of the problem, a description of the methods that you intend to use to solve the problem, how you will evaluate, and a description of the data.   Please include a timeline, and list any places where you see there may be potential issues.   Think about backup plans.   Extra-bonus-credit: identify a potential workshop or conference target, along with the deadline.  

 

Thursday, October 29

Advanced Causal Modeling techniques from Stats and Econ: BYOP

Assignment: BYOP #1: Post a pointer to paper, a VERY BRIEF : Summary, Method, Finding (SFM, :>) for your paper.   1-2 sentences for each.

 

Tuesday, November 3

Causal Models: Sprites

Reading: Spirtes, Introduction to Causal Inference (skim, focus on section 4) pdf 

Presenter: Shachi Kumar

Assignment: QCR #8, posted by noon

Reading: 

Presenter: Matt Howard

Assignment: QCR #9, posted by noon (we will likely cover this paper mostly on Thu)

 

Thursday, November 5

Causal Models for Relational Data 

Reading: 

  • C. Shalizi and A. Thomas. Homophily and contagion are generically confounded in observational social network studies. Sociological Methods and Research, 40, 2011.    pdf

Presenter: Diego Rodriguez

Assignment: QCR #10, posted by noon

 

Tuesday, November 10

Causal Relational Models

Reading:

  • B. Sinclair, M. McConnell, and D. Green. Detecting spillover effects: Design and analysis of multilevel experiments. American Journal of Political Science, 56(4), 2012.  pdf

Presenter: Rahul Talar

Assignment: QCR #11, posted by noon

 

Thursday, November 12

Causal Relational Models

Reading:

  • M. E. Maier, B. J. Taylor, H. Oktay, and D. Jensen. Learning causal models of relational domains. In Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, (AAAI), 2010. pdf

Presenter: Morteza Behrooz

Assignment: QCR #12, posted by noon

Optional Reading:

  • M. J. Rattigan, M. E. Maier, and D. Jensen. Relational blocking for causal discovery. In Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, (AAAI), 2011.  pdf

  • A Sound and Complete Algorithm for Learning Causal Models from Relational Data, http://auai.org/uai2013/prints/papers/197.pdf

 

Tuesday, November 17

P. Toulis and E. K. Kao. Estimation of causal peer influence effects. In Proceedings of the 30th International Conference on Machine Learning, ICML 2013.
http://jmlr.org/proceedings/papers/v28/toulis13.pdf
Presenter: Sriram Srinivasan
Assignment: QCR #13, posted by noon,

PROJECT UPDATE DUE -- please email me a short update on what you've done so far for your project, what you need to do still, and any issues you are encountering.

  

Thursday, November 19

Causal Models for Recommender Systems
Reading: Estimating the Causal Impact of Recommendation Systems from Observational Data, Amit Sharma, Jake M. Hofman and Duncan J. Watts, EC '15 Proceedings of the Sixteenth ACM Conference on Economics and Computation.  pdf  (alternate pdf link)

Presenter: Sabina Tomkin
Assignment: QCR #14, posted by noon 

 

Tuesday, November 24

Causal Relational Models, BYOP

 

Thursday, November 26 -- THANKSGIVING

 

Tuesday, December 1

Causal Models in NLP
Minimally Supervised Event Causality Identification, Quang Xuan Do Yee Seng Chan Dan Roth, EMNLP 2011.   pdf
Presenter: Nikhil Kini
Assignment: QCR #15, posted by noon
Helpful notes: pdf

From Infrastructure to Culture: A/B Testing Challenges in Large Scale Social Networks, Ya Xu, Nanyu Chen, Adrian Fernandez, Omar Sinno, Anmol Bhasin, KDD 2015.  pdf (from acm digital libraries); local copy pdf
Presenter: Johnathan Pagnutti
Assignment: QCR #16, posted by noon

 

Thursday, December 3

Project Posters & Party!!!

 

Wednesday, December 9

Project Writeups Due