Prediction Engines
Research around information aggregation and prediction, including polls, probability elicitation, and prediction markets.These methods, broadly defined as wisdom of the crowds, are utilized for a range of outcomes: elections, marketing, internal corporate, military intelligence, etc. We demonstrate some serious advances. (1) Combinatorial Prediction Markets: frontend, backened, and unique questions. (2) Experimental Prediction Markets and Polling. (3) Forecasts, Sentiment, and Data Analytics
Publications
- Sebastien Lahaie, Miro Dudik, David Rothschild, and David Pennock, A Combinatorial Prediction Market for the U.S. Elections, ACM Conference on Electronic Commerce, June 2013
- Jacob Abernethy, Yiling Chen, and Jennifer Wortman Vaughan, Efficient Market Making via Convex Optimization, and a Connection to Online Learning, in ACM Transactions on Economics and Computation (To appear), 2012
- Yiling Chen, Mike Ruberry, and Jennifer Wortman Vaughan, Designing Informative Securities, in 28th Conference on Uncertainty in Artificial Intelligence (UAI), 2012
- Alina Beygelzimer, John Langford, and David Pennock, Learning performance of prediction markets with Kelly bettors, International Conference on Autonomous Agents and Multiagent Systems, 2012
- Miroslav Dudik, Sebastien Lahaie, and David Pennock, A Tractable Combinatorial Market Maker Using Constraint Generation, in ACM Conference on Electronic Commerce, 2012
- David Pennock and Lirong Xia, Price updating in combinatorial prediction markets with Bayesian networks, Conference on Uncertainty in Artificial Intelligence, 2011
- Lirong Xia and David Pennock, An efficient Monte-Carlo algorithm for pricing combinatorial prediction markets for tournaments, International Joint Conference on Artificial Intelligence, 2011
- Jacob Abernethy, Yiling Chen, and Jennifer Wortman Vaughan, An Optimization-Based Framework for Automated Market-Making, in Twelfth ACM Conference on Electronic Commerce (EC), 2011
- Yiling Chen and Jennifer Wortman Vaughan, A New Understanding of Prediction Markets Via No-Regret Learning, in Eleventh ACM Conference on Electronic Commerce (EC), 2010
- Abe Othman, Tuomas Sandholm, David Pennock, and Daniel Reeves, A practical liquidity-sensitive automated market maker, 2010
People
