Defense Event
Women in Computing

All Men Count With You, But None Too Much: Information Aggregation and Learning in Prediction Markets

Sindhu Kutty

Monday, December 15, 2014
10:00am - 12:00pm
3725 Beyster Bldg.

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About the Event

Prediction markets are markets that are set up to aggregate information from a population of traders in order to predict the outcome of an event. In this thesis, we will consider the problem of designing prediction markets with discernible semantics of aggregation whose syntax is amenable to analysis. For this, we will use tools from computer science (in particular, machine learning), statistics and economics. We construct a class of market mechanisms whose predictions are based on the aggregated private beliefs of traders. We will also consider the problem in reverse: using prediction markets to design machine learning algorithms. In particular, we use the idea of sequential aggregation from prediction markets to design machine learning algorithms that are suited to situations where data arrives sequentially. We will focus on the design of algorithms for recommender systems that are robust against cloning attacks and that are guaranteed to perform well even when data is only partially available.

Additional Information

Sponsor(s): CSE

Open to: Public