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Title: Gaussian Process Models for Multitask Learning.

Abstract: Multi-task learning refers to a framework in machine learning where multiple task sharing a common domain are learned simultaneously. In this talk, I will explain how to incorporate this framework within Bayesian modelling using Gaussian process models. I will explain the general structure of a multi-output GPs, and explore some of the most common kernel structures that correspond to such models.