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My question is about the article Scalable Bayesian preference learning for crowds.

The paper describes the use of Stochastic Variational Inference (SVI) for solving the problem called Preference Learning using Gaussian Processes.

The question is about section 4.2 described in the image below taken from the article Scalable Bayesian preference learning for crowds:

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Question: Why is no longer necessary to invert a covariance matrix?

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