We propose a practical Bayesian optimization method over sets, to minimize black-box function that takes set as single input. Because inputs are permutation-invariant, traditional Gaussian process-based strategies which assume vector can fall short. To address this, we develop with kernel is used build surrogate functions. This accumulates similarity elements enforce permutation-invariance, but...