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ANC Workshop Talk: Jonathan Millin, Chair: Ioan Stanculescu

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  • ANC Workshop Talk
When May 01, 2012
from 11:00 AM to 12:00 PM
Where IF 4.31/4.33
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Jonathan Millin:

Although there are many different models in machine learning, there are very few compositional approaches (model averaging, mixtures, products/factors, mixings). Prediction markets are used effectively in real life to predict outcomes for events such as presidential elections. Market based approaches are also known to be robust (with different players entering and leaving the market all the time), scalable (millions of players interact with markets every minute) and flexible (adjusting to new information very quickly).

I will be discussing the use of prediction markets for machine learning goals, namely classifier aggregation and probability estimation. I will give a brief introduction on how prediction markets can be set in probabilistic terms, how we have formalised them from a utility based approach, and how they can be used to recreate the standard compositional structures of mixtures and products. Following this, I will compare results from different utilities function, showing how a market of inhomogeneous isoelastic utilities outperforms standard compositional structure, and show how a market of homogeneous isoelastic agents can produce equilibrium prices corresponding to alpha-mixtures.  Finally, I will discuss potential future avenues of research in the area.


David Willshaw

Unfortunately David can no longer give a talk today.