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Found 3 papers, 1 papers with code
This Too Shall Pass: Removing Stale Observations in Dynamic Bayesian Optimization
However, optimizing a black-box which is also a function of time (i. e., a dynamic function) $f : \mathcal{S} \times \mathcal{T} \to \mathbb{R}$ remains a challenge, since a dynamic Bayesian Optimization (DBO) algorithm has to keep track of the optimum over time.
Relaxing the Additivity Constraints in Decentralized No-Regret High-Dimensional Bayesian Optimization
Bayesian Optimization (BO) is typically used to optimize an unknown function $f$ that is noisy and costly to evaluate, by exploiting an acquisition function that must be maximized at each optimization step.
INSPIRE: Distributed Bayesian Optimization for ImproviNg SPatIal REuse in Dense WLANs
WLANs, which have overtaken wired networks to become the primary means of connecting devices to the Internet, are prone to performance issues due to the scarcity of space in the radio spectrum.
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