Schedule is tentative and may be adjusted as the course proceeds.

#	Date	Topics and Readings	Extra Readings	Reading Questions	Presenter
1	1/25	Introduction	Lecture Slides		Yiling
2	1/27	Game Theory and Decision Theory Review Chapter 3, Chapter 6 (6.3 only). Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations, by Y. Shoham and K. Leyton-Brown (2009).	Lecture Slides Chapter 5 (5.1, 5.2 only) and Chapter 6 (6.1.1, 6.1.2 only). Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations, by Y. Shoham and K. Leyton-Brown (2009).		Yiling
Scoring Rules and Elicitation
3	2/1	Proper Scoring Rules Elicitation of Personal Probabilities and Expectations. L. J. Savage, Journal of the American Statistical Association, 66(336):783-801, 1971. Strictly Proper Scoring Rules, Prediction, and Estimation. T. Gneiting and A. E. Raftery, Journal of the American Statistical Association, 2007. (Read Section 1 and Section 3.1. The rest is optional.)	Lecture Slides GR'07, LPS'08, Selten'98, HB'71, WM'68,McCarthy'56, Brier'50	RQs	Yiling
4	2/3	Peer Prediction Eliciting Honest Feedback: The Peer-Prediction Method, N. Miller, P. Resnick, and R. Zeckhauser, Management Science, 51(9): 1359-1373, 2005. (Read sections 1 and 2. The rest is optional.) Crowdsourced Judgement Elicitation with Endogenous Proficiency, A Dasgupta, and A. Ghosh. WWW'13.	Presentation Slides JF'06, JF'07, JF'08, JR'09, PRGJ'08, WP'12	RQs	Charles and Virgile
5	2/8	Property Elicitation Making and Evaluating Point Forecasts. Journal of the American Statistical Association, Vol. 106, No. 494, June 2011. Eliciting Properties of Probability Distributions. Lambert, Pennock and Shoham, ACM EC'08. (Read sections 1-3. The rest is optional.)	Presentation Slides Lambert'13, LS'09	RQs	Ben and Paul
6	2/10	Property Elicitation (Cont.) On Elicitation Complexity, R.M. Frongillo and I.A. Kash, NIPS'15.	Presentation Slides FK-COLT'15, AA'15	RQs	Bo
	2/15	Presidents Day, no class
Prediction Markets, Online Learning, and Games
7	2/17	Prediction Markets and Market Scoring Rules The Promise of Prediction Markets, K.J. Arrow et. al., Science, 320, p.877, May 16 2008. Logarithmic Market Scoring Rules for Modular Combinatorial Information Aggregation, R. Hanson, Journal of Prediction Markets, 1(1):3-15, 2007. David Pennock's blog on how to implement market scoring rules as a market maker.	Lecture Slides BFNR'01, CP'02, CFH'03, CWZ'08, OS'10, Hanson'03, DPAIWCNJ'15	RQs	Lecture
8	2/22	Introduction to Online Learning The Multiplicative Weights Update Method, S. Arora, E. Hazan and S. Kale. Theory of Computing, vol. 8, pp. 121-164, 2012. (Read Sections 1, 2, 3.1 and 3.8 , 3.9. and 4. The rest is optional.)	Lecture Slides S-S online learning survey, RS Lecture Notes	RQs	Lecture
9	2/24	Automated Market Makers and Online Learning Efficient Market Making via Convex Optimization, and a Connection to Online Learning, J. Abernethy, Y. Chen, and J.W. Vaughan, ACM TEAC, 2013. (Please feel free to skim Section 5 and Section 6 lightly. Those two won't constitute the focus of our discussion.)	Presentation Slides CP'07, OPRS'10, OS'11, CRV'13, LV'13, AFLV'14, DFV'14, HLPV'15	RQs	Dev and Jetlir
10	2/29	Aggregation in Prediction Markets (w/ connection to exponential family) Information aggregation in exponential family markets. J. Abernethy, S. Kutty, S. Lahaie, and R. Sami. ACM EC'14.	Presentation Slides Survey on connections of market makers, exponential family, and risk measures: AFK'14 Prices or equilibrium in prediction markets: SV'15, FP'12, Manski'06, WZ'07, Ostrovsky'13, CRV'12, CDHRPHFG'10, IGM'11, GZC'13,	RQs	Colin and Anson
11	3/2	Learning in Games I The Multiplicative Weights Update Method, S. Arora, E. Hazan and S. Kale. Theory of Computing, vol. 8, pp. 121-164, 2012. (Read Section 3.2.) Chapter 4 of Algorithmic Game Theory. N. Nisan, T. Roughgarden, E. Tardos, V.V. Vazirani (Editors), Cambridge University Press, 2007. (Focus on 4.4 and onward.)	Lecture Slides FS'99, BM'07	RQs	Lecture
12	3/7	Learning in Games II Fast Convergence of Regularized Learning in Games, V. Syrgkanis, A. Agarwal, H. Luo, R.E. Schapire, NIPS 2015		RQs	Brendan
13	3/9	Learning and Security Games Commitment Without Regrets: Online Learning in Stackelberg Security Games. M.-F. Balcan, A. Blum, N. Haghtalab, and A. D. Procaccia, ACM EC'15.	Presentation slides BHP'14, LCM'09	RQs	Tom and Varun
	3/14	Spring Break, no class
	3/16	Spring Break, no class
Batch Learning, with Strategic Considerations
14	3/21	Introduction to PAC Learning Chapter 1 in An Introduction to Computational Learning Theory. M. J. Kearns and U. Vazirani.		RQs	Lecture
15	3/23	Strategy-proof Machine Learning Algorithms for strategy proof classification, R. Meir, A.D. Procaccia, J.S. Rosenschein, Artificial Intelligence, 2012.	Presentation slides DFP'10	RQs	Yaoguang
16	3/28	Learning As a Game Linear Regression as a Non-Cooperative Game. S. Ioannidis and P. Loiseau. WINE'13.	Presentation slides JP'04	RQs	Katherine and Jonah
17	3/30	Strategic Data Sources and Learning I Strategic Classification. M. Hardt, N. Megiddo, C. Papadimitriou, and M. Wootters, ITCS'16.	Presentation slides BS'11, BKS'12,	RQs	Jetlir and Yaoguang
18	4/4	Strategic Data Sources and Learning II Conducting Truthful Surveys Cheaply, A. Roth and G. Schoenebeck, ACM EC'12.	ACHW'15	RQs	Andre and George
19	4/6	Strategic Data Sources and Learning III Optimum Statistical Estimation with Strategic Data Sources. Y. Cai, C. Daskalakis, and C. Papadimitriou. COLT'15.	Presentation slides HIM'13	RQs	Tiffany and Jimmy
20	4/11	Privacy-aware Data Sources Truthful Linear Regression, R. Cummings, S. Ioannidis, and K. Ligett. COLT'15. Selling Privacy at Auction, A. Ghosh and A. Roth, EC'11.	FL'12, GR'12, GLRS'14, CLRWZ'15	RQs	Dev
21	4/13	Scoring Rules and Markets for Data Elicitation Nonparametric Scoring Rules. E. Zawadzki and S. Lahaie AAAI'15. A Market Framework for Eliciting Private Data, B. Waggoner, R. Frongillo, and A. Abernethy, NIPS'15. (This reading is optional.)	Presentation slides AF'11	RQs	Bo
A Statistical Perspective
22	4/18	Learning and Econometrics Game Theory and Econometrics: A Survey of Some Recent Research, P. Bajari, H. Hong, and D. Nekipelov, Econometric Society World Congress 2010. (Sections 1-4 only. Other sections optional.) Big Data, New Tricks for Econometrics, H.R. Varian, Journal of Economic Perspectives, 2014.	BNRY'15, AI'15, Athey'15	RQs	Katherine and Jonah
23	4/20	Incentives and Statistical Inference Incentive Compatible Experimental Design, P. Toulis, D.C. Parkes, E. Pfeffer, and J. Zou, ACM EC'15.		RQs	Panos Toulis
24	4/25	Rationalization of Voting Rules Common Voting Rules as Maximum Likelihood Estimators, V. Conitzer and T. Sandholm, UAI 2005.	XC'11, CRX'09, EFS'09, EFS'10a, EFS'10b	RQs	Tom and Varun
25	4/27	Project presentations