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![]() Bayesian RankingAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Zoubin Ghahramani. Advanced Machine Learning Tutorial Lecture In this talk I will present a Bayesian approach to ranking a set of objects based on the possibly partial or noisy rankings of small subsets of objects. Rankings are represented by assigning a latent real-valued variable (skill, urgency, value) to each object and sorting the objects according to the magnitude of the latent variables. The system maintains a Gaussian belief about the value of each object in terms of mean and variance. I will discuss approximate message passing in factor graphs as the computational technique to address the problem of inference. After presenting theoretical and algorithmic aspects of the system, I will outline two applications:
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