Research Topics & Interests Fundamental HPO We explore core research topics in hyperparameter optimization, including black-box optimization with Bayesian Optimization, known for its sample efficiency and flexibility, user priors, which integrate human knowledge to guide optimization processes. Additionally, we investigate learning curve extrapolation and multi-fidelity optimization approaches to accelerate optimization and enable more efficient resource … Continue reading Hyperparameter Optimization