RIKEN AIP (Nihombashi) Open area
Title: Probabilistic Modelling With the Experts
Samuel Kaski
Finnish Center for Artificial Intelligence FCAI
Abstract: I will discuss multiple-data-source prediction and modelling problems arising in a number of fields, for instance in omics-based precision medicine. What is less typical is that some of the data sources are experts, whose time is costly, changing the problem to active learning for prediction. We have addressed this setup as a probabilistic modelling problem, where different types of sources need different modelling assumptions. I will demonstrate that promising results can be achieved in treatment effectiveness prediction tasks in restricted settings, even by explaining human variation with noise models. Richer behaviour requires richer models that draw from cognitive science.
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