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