Crowd IQ -- Aggregating Opinions to Boost Performance

Autor: Kosinski, Michal, Bachrach, Yoram, Graepel, Thore, Kasneci, Giergji, Van Gael, Jurgen

We show how the quality of decisions based on the aggregated opinions of the crowd can be conveniently studied using a sample of individual responses to a standard IQ questionnaire. We aggregated the responses to the IQ questionnaire using simple maj

Externí odkaz: http://arxiv.org/abs/2410.10004

Measure Transformer Semantics for Bayesian Machine Learning

Autor: Borgström, Johannes, Gordon, Andrew D, Greenberg, Michael, Margetson, James, Van Gael, Jurgen

Publikováno v: Logical Methods in Computer Science, Volume 9, Issue 3 (September 9, 2013) lmcs:815

The Bayesian approach to machine learning amounts to computing posterior distributions of random variables from a probabilistic model of how the variables are related (that is, a prior distribution) and a set of observations of variables. There is a

Externí odkaz: http://arxiv.org/abs/1308.0689

Measure Transformer Semantics for Bayesian Machine Learning.

Autor: Borgström, Johannes, Gordon, Andrew D., Greenberg, Michael, Margetson, James, Van Gael, Jurgen

Publikováno v: Programming Languages & Systems: 20th European Symposium on Programming, ESOP 2011, Held as Part of the Joint European Conferences on Theory & Practice of Software, ETAPS 2011, Saarbrücken, Germany, March 26-April 3, 2011. Proceedings; 2011, p77-96, 20p

Bayesian Knowledge Corroboration with Logical Rules and User Feedback.

Autor: Kasneci, Gjergji, Van Gael, Jurgen, Herbrich, Ralf, Graepel, Thore

Publikováno v: Machine Learning & Knowledge Discovery in Databases (9783642158827); 2010, p1-18, 18p