A Very Brief Introduction to Gaussian Process and Bayesian Optimization
Gaussian Process Big Picture and Background Intuitively, Gaussian distribution define the state space, while Gaussian Process define the function space Before we introduce Gaussian process, we should understand Gaussian distriution at first. For a RV(random variable) $X$ that follow Gaussian Distribution $\mathcal{N}(0, 1)$ should be following image: The P.D.F should be $$x \sim \mathcal{N}(\mu, \sigma) = \frac{1}{\sigma \sqrt{2 \pi}} e^{- \frac{1}{2} (\frac{- \mu}{\sigma})^2}$$ As for Multivariate Gaussian Distribution, given 2 RV $x$, $y$ both 2 RV follow Gaussian Distribution $\mathcal{N}(0, 1)$ we can illustrate it as...