Abstract This package implements a modified Constrained Adversarially Robust Bayesian Optimization (CARBO) sampler based on the paper Constrained robust Bayesian optimization of expensive noisyblack-box functions with guaranteed regret bounds. This sampler robustly optimizes a function along with inequality constraints that incurs a noise in its input. The algorithm details are described in the Others section.
APIs CARBOSampler(*, seed: int | None = None, independent_sampler: BaseSampler | None = None, n_startup_trials: int = 10, deterministic_objective: bool = False, constraints_func: Callable[[FrozenTrial], Sequence[float]] | None = None, rho: float = 1e3, beta: float = 4.