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Wednesday 04 December 2019, 14:00-15:30
Scalable Gaussian Processes
- đ¤ Speaker: David Burt, Andrew Foong
- đ Date & Time: Wednesday 04 December 2019, 14:00 - 15:30
- đ Venue: Engineering Department, CBL Room BE-438
Questions? Contact
Robert Pinsler
Abstract
Inference and learning in models with Gaussian process (GP) priors are well-known to suffer from high computational costs, both in terms of time and memory. Various methods have been proposed to allow GP models to scale to big data. In this reading group, we discuss two popular techniques for scaling up GP models: variational inference and conjugate gradient methods.
Series This talk is part of the Machine Learning Reading Group @ CUED series.
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