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Pavel Erofeev edited GP.tex
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\subsection{Gaussain Processes}
\label{sec:GaussinaProcesses}
In this paper we consider a specific class of regression functions $\mathcal{GP}$ -- Gaussian Processes. Any process $g\in\mathcal{GP}$ is uniqely defined by its mean $\mu(\mathbf{x}) = \mathrm{E}\left[f(\mathbf{x})\right]$ and covariance $\mathrm{Cov}(y,
y\prime) y^\prime) = k(\mathbf{x},
\mathbf{x}\prime) \mathbf{x}^\prime) = \mathrm{E}\left[(f(\mathbf{x}) - \mu(\mathbf{x}))
(f(\mathbf{x}\prime) (f(\mathbf{x}^\prime) -
\mu(\mathbf{x}\prime))\right]$ \mu(\mathbf{x}^\prime))\right]$ functions.
Гауссовский процесс является одним из возможных способов задания распределения на пространстве функций.