The purpose of this paper is twofold. On one side, we present a general framework for Bayesian optimization and we compare it with some related fields in active learning and Bayesian numerical analysis. On the other hand, Bayesian optimization and related problems (bandits, sequential experimental design) are highly dependent on the surrogate model that is selected. However, there is no clear s...

We consider the problem of jointly testing multiple hypotheses and estimating a random parameter underlying distribution. This is investigated in sequential setup under mild assumptions on process. The optimal method minimizes expected number samples while ensuring that average detection/estimation errors do not exceed certain level. After converting constrained to an unconstrained one, we char...

In this paper, we investigate a cooperative spectrum sharing mechanism realized by a dynamic Bayesian spectrum bargaining between a pair of non-myopic primary user and secondary user. The primary user has only incomplete information of the secondary user’s energy cost. We model such a bargaining process as a dynamic Bayesian game, and discuss the equilibria under all possible system parameters....