We propose a novel sparse spectrum approximation of Gaussian process (GP) tailored for Bayesian optimization (BO). Whilst the current methods provide desired approximations regression problems, it is observed that this particular form generates an overconfident GP, i.e., produces less epistemic uncertainty than original GP. Since balance between predictive mean and variance key determinant to s...