Bayesian Optimization with Cost-varying Variable Subsets Sebastian Shenghong Tay

Neural Information Processing Systems 

We introduce the problem of Bayesian optimization with cost-varying variable subsets (BOCVS) where in each iteration, the learner chooses a subset of query variables and specifies their values while the rest are randomly sampled.

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