Multitask learning: the Bayesian way

Posted in Science on September 07, 2008

Multitask learning: the Bayesian way

Multi-task learning lends itself particularly well to a Bayesian approach. Cross-inference between tasks can be implemented by sharing parameters in the likelihood model and the prior for the task-specific model parameters. Choosing different priors, one can implement task clustering and task gating. Throughout my presentation, predicting single-copy newspaper sales will serve as a running example.

Author: Tom Heskes, Radboud University Nijmegen

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Tags: Science, Lectures, Computer Science, Machine Learning, VideoLectures.Net, Bayesian Learning