Uncertainties Need a Purpose

Uncertainties Need a Purpose

Abstract

I argue that the task a model will be used for should be an explicit part of the modelling process. As an example, I show how ideas from Bayesian Optimization and Probabilistic Numberics can be used to reinterpret Reinforcement Learning.

Type
Publication
Workshop on Uncertainty in Composite Models
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Markus Kaiser
PhD candidate in Bayesian Machine Learning

My research interests include hierarchical Bayesian modelling, Gaussian Processes and scalable Bayesian Inference.