Machine Learning Markets
published: Jan. 25, 2012, recorded: December 2011, views: 6092
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Prediction markets show considerable promise for developing flexible mechanisms for machine learning. Here, machine learning markets for multivariate systems are defined, and a utility-based framework is established for their analysis. This differs from the usual approach of defining static betting functions. It is shown that such markets can implement model combination methods used in machine learning, such as product of expert and mixture of expert approaches as equilibrium pricing models, by varying agent utility functions. They can also implement models composed of local potentials, and message passing methods. Prediction markets also allow for more flexible combinations, by combining multiple different utility functions. Conversely, the market mechanisms implement inference in the relevant probabilistic models. This means that market mechanism can be utilized for implementing parallelized model building and inference for probabilistic modelling.
Download slides: nipsworkshops2011_storkey_markets_01.pdf (2.3 MB)
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !
Reviews and comments:
In the event that you expected to make yourself an extraordinarily energetic individual, you would effectively begin dating young people on a dating site. There are the most magnificent youths who will dependably talk with you about adoration. The way that now you can http://mailorderbridereview.com/ locate a young lady, by then in the event that you required, you would locate the most grand and get hitched
Write your own review or comment: