Gradient-Free-Optimizers is a Python library for gradient-free optimization of black-box functions. It provides a unified interface to 23 optimization algorithms, from simple hill climbing to Bayesian ...

SMAC offers a robust and flexible framework for Bayesian Optimization to support users in determining well-performing hyperparameter configurations for their (Machine Learning) algorithms, datasets ...

Have you ever heard the term Bayesian optimization? It is a very important concept in the world of machine learning and AI, but it might feel a bit difficult for those hearing it for the first time.

Identifying lithology is crucial for geological exploration, and the adoption of artificial intelligence is progressively becoming a refined approach to automate this process. A key feature of this ...

Hyperparameter optimization is crucial for enhancing machine learning models. It involves selecting the right set of parameters to achieve the best performance. Optimizing hyperparameters can ...

School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, U.K. School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, U.K. The Alan Turing Institute, London NW1 2DB, U.K. School ...