Algorithm Configuration

Given a parameterized algorithm \mathcal{A} with possible parameter settings \mathcal{C}, a set of training problem instances \mathcal{I}, and a performance metric m: \mathcal{I} \times \mathcal{C} \rightarrow \mathbb{R}, the algorithm configuration problem is to find a parameter configuration c \in \mathcal{C} that minimizes m across the instances in \mathcal{I}.

Workflow of Algorithm Configuration

Literature

Configurators

Hyperparameter Optimization