Fast methods for training Gaussian processes on large datasets
نویسندگان
چکیده
منابع مشابه
Fast methods for training Gaussian processes on large datasets
Gaussian process regression (GPR) is a non-parametric Bayesian technique for interpolating or fitting data. The main barrier to further uptake of this powerful tool rests in the computational costs associated with the matrices which arise when dealing with large datasets. Here, we derive some simple results which we have found useful for speeding up the learning stage in the GPR algorithm, and ...
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ژورنال
عنوان ژورنال: Royal Society Open Science
سال: 2016
ISSN: 2054-5703
DOI: 10.1098/rsos.160125