Abstract: We propose a novel Evolutionary Algorithm (EA) based on the Differential Evolution algorithm for solving global numerical optimization problem in real-valued continuous parameter space. The ...

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.

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 ...

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 ...

Technological advances and the need for new polymers necessitate continuous research in the design and identification of polymers with specific physical and chemical properties. Among the different ...