- Alain-Sol Sznitman. Topics in propagation of chaos. In Ecole d’eÌteÌ de probabiliteÌs de SaintFlour XIX1989, pages 165–251. Springer, 1991.
Paper not yet in RePEc: Add citation now
- Amir Beck and Marc Teboulle. Mirror descent and nonlinear projected subgradient methods for convex optimization. Operations Research Letters, 31(3):167–175, 2003.
Paper not yet in RePEc: Add citation now
- Arnold C Harberger. The measurement of waste. The American Economic Review, pages 58–76, 1964.
Paper not yet in RePEc: Add citation now
- Ashish Khetan and Sewoong Oh. Achieving budget-optimality with adaptive schemes in crowdsourcing. In Advances in Neural Information Processing Systems, pages 4844–4852, 2016.
Paper not yet in RePEc: Add citation now
- Benjamin Letham, Brian Karrer, Guilherme Ottoni, and Eytan Bakshy. Constrained Bayesian optimization with noisy experiments. Bayesian Analysis, 2018.
Paper not yet in RePEc: Add citation now
- CAISO. Renewable resources and the California electric power industry: System operations, wholesale markets and grid planning. California ISO Report, 2009.
Paper not yet in RePEc: Add citation now
- Carl Graham and Sylvie MeÌleÌard. Chaos hypothesis for a system interacting through shared resources. Probability Theory and Related Fields, 100(2):157–174, 1994.
Paper not yet in RePEc: Add citation now
Charles A Holt and Susan K Laury. Risk aversion and incentive effects. American economic review, 92(5):1644–1655, 2002. Michael G Hudgens and M Elizabeth Halloran. Toward causal inference with interference.
Charles F Manski. Identification of treatment response with social interactions. The Econometrics Journal, 16(1):S1–S23, 2013. Laurent MassoulieÌ and Kuang Xu. On the capacity of information processing systems.
- Charles M Stein. Estimation of the mean of a multivariate normal distribution. The annals of Statistics, pages 1135–1151, 1981. Alexander L Stolyar. Pull-based load distribution in large-scale heterogeneous service systems.
Paper not yet in RePEc: Add citation now
Dean Eckles, Brian Karrer, and Johan Ugander. Design and analysis of experiments in networks: Reducing bias from interference. Journal of Causal Inference, 5(1), 2017.
- Diane Tang, Ashish Agarwal, Deirdre O’Brien, and Mike Meyer. Overlapping experiment infrastructure: More, better, faster experimentation. In Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining, pages 17– 26. ACM, 2010.
Paper not yet in RePEc: Add citation now
- Francesco Orabona, Koby Crammer, and Nicolo Cesa-Bianchi. A generalized online mirror descent with applications to classification and regression. Machine Learning, 99(3):411– 435, 2015.
Paper not yet in RePEc: Add citation now
Gerard P Cachon, Kaitlin M Daniels, and Ruben Lobel. The role of surge pricing on a service platform with self-scheduling capacity. Manufacturing & Service Operations Management, 19(3):368–384, 2017.
Guido W Imbens and Donald B Rubin. Causal Inference in Statistics, Social, and Biomedical Sciences. Cambridge University Press, 2015.
Guillaume W Basse, Avi Feller, and Panos Toulis. Randomization tests of causal effects under interference. Biometrika, 2019.
- Guillaume W Basse, Hossein Azari Soufiani, and Diane Lambert. Randomization and the pernicious effects of limited budgets on auction experiments. In Artificial Intelligence and Statistics, pages 1412–1420, 2016.
Paper not yet in RePEc: Add citation now
- In Conference on Learning Theory, pages 3–24, 2013.
Paper not yet in RePEc: Add citation now
- In Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms, pages 385–394. Society for Industrial and Applied Mathematics, 2005.
Paper not yet in RePEc: Add citation now
- James C Spall. Introduction to stochastic search and optimization: estimation, simulation, and control, volume 65. John Wiley & Sons, 2005.
Paper not yet in RePEc: Add citation now
- Joel Spencer, Madhu Sudan, and Kuang Xu. Queuing with future information. Annals of Applied Probability, 24(5):2091–2142, 2014.
Paper not yet in RePEc: Add citation now
- John C Duchi, Michael I Jordan, Martin J Wainwright, and Andre Wibisono. Optimal rates for zero-order convex optimization: The power of two function evaluations. IEEE Transactions on Information Theory, 61(5):2788–2806, 2015.
Paper not yet in RePEc: Add citation now
- John N Tsitsiklis and Kuang Xu. On the power of (even a little) resource pooling. Stochastic Systems, 2(1):1–66, 2012.
Paper not yet in RePEc: Add citation now
- John W Pratt. Risk aversion in the small and in the large. In Uncertainty in Economics, pages 59–79. Elsevier, 1978. Ohad Shamir. On the complexity of bandit and derivative-free stochastic convex optimization.
Paper not yet in RePEc: Add citation now
- Jonathan Hall, Cory Kendrick, and Chris Nosko. The effects of ubers surge pricing: A case study. The University of Chicago Booth School of Business, 2015.
Paper not yet in RePEc: Add citation now
- Jonathan V Hall, John J Horton, and Daniel T Knoepfle. Pricing efficiently in designed markets: The case of ride-sharing. 2019.
Paper not yet in RePEc: Add citation now
Kenneth E Train. Discrete choice methods with simulation. Cambridge university press, 2009.
- Kevin G Jamieson, Robert Nowak, and Ben Recht. Query complexity of derivative-free optimization. In Advances in Neural Information Processing Systems, pages 2672–2680, 2012.
Paper not yet in RePEc: Add citation now
Krishnamurthy Iyer, Ramesh Johari, and Mukund Sundararajan. Mean field equilibria of dynamic auctions with learning. Management Science, 60(12):2949–2970, 2014.
- LeÌon Bottou, Jonas Peters, Joaquin Quinonero Candela, Denis Xavier Charles, Max Chickering, Elon Portugaly, Dipankar Ray, Patrice Y Simard, and Ed Snelson. Counterfactual reasoning and learning systems: The example of computational advertising. Journal of Machine Learning Research, 14(1):3207–3260, 2013.
Paper not yet in RePEc: Add citation now
- Marc MeÌzard, Giorgio Parisi, and Miguel Virasoro. Spin glass theory and beyond: An Introduction to the Replica Method and Its Applications, volume 9. World Scientific Publishing Company, 1987. Yurii Nesterov and Vladimir Spokoiny. Random gradient-free minimization of convex functions.
Paper not yet in RePEc: Add citation now
- Mark Goh. Congestion management and electronic road pricing in singapore. Journal of transport geography, 10(1):29–38, 2002.
Paper not yet in RePEc: Add citation now
- Maury Bramson, Yi Lu, and Balaji Prabhakar. Asymptotic independence of queues under randomized load balancing. Queueing Systems, 71(3):247–292, 2012.
Paper not yet in RePEc: Add citation now
Michael E Sobel. What do randomized studies of housing mobility demonstrate? causal inference in the face of interference. Journal of the American Statistical Association, 101 (476):1398–1407, 2006.
- Michael Ostrovsky and Michael Schwarz. Reserve prices in internet advertising auctions: a field experiment. EC, 11:59–60, 2011.
Paper not yet in RePEc: Add citation now
- Nicolo Cesa-Bianchi, Alex Conconi, and Claudio Gentile. On the generalization ability of on-line learning algorithms. IEEE Transactions on Information Theory, 50(9):2050–2057, 2004.
Paper not yet in RePEc: Add citation now
- Nikita Dmitrievna Vvedenskaya, Roland L’vovich Dobrushin, and Fridrikh Izrailevich Karpelevich. Queueing system with selection of the shortest of two queues: An asymptotic approach. Problemy Peredachi Informatsii, 32(1):20–34, 1996. A Proofs A.1 Proof of Proposition 9 We start by verifying a useful property that applies to any exponential family with discrete support. Definition 11. Let tXu a family of discrete random variables and parameterized by θ P Θ Ă R. We say that tXu is an exponential family, if the probability mass function (PMF) fθ for X can be expressed as fθpxq “ hpxq exppηpθqTpxq Apθqq, x P Z. (A.1) where Tpq is referred to as the sufficient statistic, and ηpθq the natural parameter.
Paper not yet in RePEc: Add citation now
- Peter M Aronow and Cyrus Samii. Estimating average causal effects under general interference, with application to a social network experiment. The Annals of Applied Statistics, 11(4):1912–1947, 2017.
Paper not yet in RePEc: Add citation now
Raj Chetty. Sufficient statistics for welfare analysis: A bridge between structural and reduced-form methods. Annual Review of Economics, 1(1):451–488, 2009.
- Ramesh Johari, Vijay Kamble, and Yash Kanoria. Matching while learning. In Proceedings of the 2017 ACM Conference on Economics and Computation, pages 119–119. ACM, 2017a.
Paper not yet in RePEc: Add citation now
- Robert D Kleinberg. Nearly tight bounds for the continuum-armed bandit problem. In Advances in Neural Information Processing Systems, pages 697–704, 2005.
Paper not yet in RePEc: Add citation now
- Ron Kohavi, Roger Longbotham, Dan Sommerfield, and Randal M Henne. Controlled experiments on the web: survey and practical guide. Data mining and knowledge discovery, 18(1):140–181, 2009.
Paper not yet in RePEc: Add citation now
- Ronald A Fisher. The Design of Experiments. Oliver and Boyd, Edinburgh, 1935. Abraham D Flaxman, Adam Tauman Kalai, Adam Tauman Kalai, and H Brendan McMahan. Online convex optimization in the bandit setting: gradient descent without a gradient.
Paper not yet in RePEc: Add citation now
- Saeed Ghadimi and Guanghui Lan. Stochastic first-and zeroth-order methods for nonconvex stochastic programming. SIAM Journal on Optimization, 23(4):2341–2368, 2013.
Paper not yet in RePEc: Add citation now
- SeÌbastien Bubeck, Yin Tat Lee, and Ronen Eldan. Kernel-based methods for bandit convex optimization. In Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, pages 72–85. ACM, 2017.
Paper not yet in RePEc: Add citation now
Shlomo Halfin and Ward Whitt. Heavy-traffic limits for queues with many exponential servers. Operations research, 29(3):567–588, 1981.
Susan Athey and Michael Luca. Economists (and economics) in tech companies. Journal of Economic Perspectives, 33(1):209–30, 2019. Susan Athey, Dean Eckles, and Guido W Imbens. Exact p-values for network interference.
- Thomas Blake and Dominic Coey. Why marketplace experimentation is harder than it seems: The role of test-control interference. In Proceedings of the fifteenth ACM conference on Economics and computation, pages 567–582. ACM, 2014.
Paper not yet in RePEc: Add citation now
- Yash Kanoria and Hamid Nazerzadeh. Dynamic reserve prices for repeated auctions: Learning from bids. Available at SSRN 2444495, 2017.
Paper not yet in RePEc: Add citation now
- Zhe Feng, Chara Podimata, and Vasilis Syrgkanis. Learning to bid without knowing your value. In Proceedings of the 2018 ACM Conference on Economics and Computation, pages 505–522. ACM, 2018.
Paper not yet in RePEc: Add citation now