Model-based Hyperparameter Optimization for Machine Learning Algorithms on Large Datasets
In my master thesis I developed model-based approach to multi-fidelity optimization. This approach allows to find promising hyperparameter configurations faster by evaluating the ml algorithm on small samples of the data.