When trained with λ on training data T train , the validation accuracy on T valid is denoted as L(λ, T train , T valid ).
in terms of time per iteration, the full Bayesian Optimization is the most expensive, taking more than twice amount of time over subset variant algorithm, while the multi-stage is 23% and 50% faster than standard Bayesian Optimization on QA and Yelp (Table 3), respectively, while maintaining the same accuracy as full Bayesian Optimization.