Samuel Kaski: Probabilistic Modelling with Experts

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 common 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, expert user models ultimately drawing from cognitive science. This brings links to other lines of work on interactive intent modelling and likelihood-free inference to infer the user models.

Date
Oct 4, 2019 10:30 AM — 11:30 AM
Event
SML Seminar
Location
LT 139 (Huxley), Imperial College London

Bio

Samuel Kaski, Finnish Center for Artificial Intelligence FCAI, Aalto University, Finland
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Marc Deisenroth
DeepMind Chair in Artificial Intelligence